EP3803413A1 - Procédés et systèmes d'analyse et d'imagerie du protéome - Google Patents

Procédés et systèmes d'analyse et d'imagerie du protéome

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Publication number
EP3803413A1
EP3803413A1 EP19739420.8A EP19739420A EP3803413A1 EP 3803413 A1 EP3803413 A1 EP 3803413A1 EP 19739420 A EP19739420 A EP 19739420A EP 3803413 A1 EP3803413 A1 EP 3803413A1
Authority
EP
European Patent Office
Prior art keywords
sample
proteins
protein
tissue
cells
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP19739420.8A
Other languages
German (de)
English (en)
Inventor
Paul D. Piehowski
Ying Zhu
Ryan T. Kelly
Kristin E. Burnum-Johnson
Ronald J. Moore
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Battelle Memorial Institute Inc
Original Assignee
Battelle Memorial Institute Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US15/993,949 external-priority patent/US11719702B2/en
Application filed by Battelle Memorial Institute Inc filed Critical Battelle Memorial Institute Inc
Publication of EP3803413A1 publication Critical patent/EP3803413A1/fr
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6842—Proteomic analysis of subsets of protein mixtures with reduced complexity, e.g. membrane proteins, phosphoproteins, organelle proteins

Definitions

  • Embodiments of the disclosure relate generally to systems and methods for proteome analysis and particularly to proteome high-throughput analysis and/or imaging.
  • MS Mass spectrometry
  • compositions and methods for processing and analysis of small cell populations and biological samples e.g., a robotically controlled chip-based nanodroplet platform.
  • the methods described herein can reduce total processing volumes from conventional volumes to nanoliter volumes within a single reactor vessel (e.g., within a single droplet reactor) while minimizing losses, such as due to sample evaporation.
  • Embodiments described herein can provide advantages over existing methods, which can require samples including a minimum of thousands of cells to provide in-depth proteome profiling. As described herein, embodiments of the disclosure can dramatically enhance the efficiency and recovery of sample processing through downscaling total processing volumes to the nanoliter range, while substantially avoiding sample loss.
  • the platform may include at least one reactor vessel having one or more hydrophilic surfaces configured for containment of the biological sample, wherein the hydrophilic surfaces have a non- zero, total surface area less than 25 mm 2 .
  • the hydrophilic surfaces of the at least one reactor vessel have a total surface area of less than 1 mm 2 .
  • the method includes transferring a first volume (e.g., a non-zero amount less than 1000 nL) of the biological sample to a single reactor vessel.
  • the methods include processing the biological sample in the single reactor vessel to yield a processed sample, and collecting a second volume of the processed sample (e.g., the second volume is a fraction of the first volume ranging from about 10 to about 100%).
  • the biological sample can include at least one of tissues, biopsies, cell homogenates, cell fractions, cultured cells, non-cultured cells, whole blood, plasma, and biological fluids.
  • the biological sample is less than 1000 nL. In other embodiments, the biological sample is less than 100 nL.
  • the methods of obtaining the biological sample may include, for example, dispensing cellular material from suspension and fluorescence- activated cell sorting.
  • the method may further comprise at least two reactor vessels, wherein the at least two reactor vessels are separated by a hydrophobic surface.
  • the biological sample for the methods described herein may include a non-zero amount of cells less than 5000 cells, less than 100 cells or less than 10 cells.
  • the methods described herein further include analyzing the collected second volume (e.g., the second volume is a fraction of the first volume ranging from about 10 to about 100 %) of the processed biological sample, and the analyzing step is configured to identify at least one unique species within the processed biological sample.
  • the analyzing step identifies at least 1,000 unique species, at least 3,000 unique species, or at least 5,000 unique species. In various embodiments, analyzing can identify greater than 3,000 unique species from 10 or less cells.
  • the unique species may include at least one of proteins or fragments thereof, lipids, or metabolites.
  • the methods described herein further include analyzing the collected second volume, and wherein the analyzing step comprises mass spectrometry or flow cytometry.
  • the platform of the methods described herein includes a glass chip.
  • the glass chip is pre-coated, e.g., with chromium, aluminum, or gold.
  • the glass chip includes a substrate containing the at least one reactor vessel, a spacer containing an aperture positioned on the substrate, and a cover positioned on the spacer, wherein the aperture is dimensioned to surround the at least one reactor vessel when the spacer is positioned on the substrate.
  • the steps involving dispensing and aspiration of sample and processing reagents are performed in a humidity-controlled chamber (e.g., which is maintained from about 80% to about 95%.
  • the methods described herein include processing the biological sample.
  • Processing the biological sample may include at least one of cell lysis, analyte extraction and solubilization, denaturation, reduction, alkylation, chemical and enzymatic reactions, concentration, and incubation.
  • the methods described herein include collecting the processed sample into a capillary.
  • collecting the processed sample into a capillary includes aspirating the processed sample into the capillary and washing the single reactor vessel with a solvent.
  • the capillary may be sealed from the external environment after the processed sample is collected therein.
  • the methods described herein include biological samples comprising of tissues.
  • the tissue can include laser-capture microdissected tissues, e.g., having dimensions less than about 1 mm.
  • a platform for biological sample preparation including a substrate with at least one reactor vessel having one or more hydrophilic surfaces configured for containment of a biological sample.
  • the hydrophilic surfaces have a non-zero total surface area less than 25 mm 2 or less than 5 mm 2 .
  • the platform includes a spacer containing an aperture, wherein the aperture is dimensioned to surround the at least one reactor vessel when the spacer is positioned on the substrate; and a cover positioned on the spacer.
  • the platform further includes a membrane interposed between the spacer and the cover, the membrane configured to form a gas-tight seal between the spacer and the cover to minimize evaporation.
  • the platform may be formed from a material that is substantially optically transparent (e.g., glass).
  • the platform may include at least one hydrophobic surface surrounding the at least one reactor vessel.
  • the platform described herein may further include at least two reactor vessels, wherein the at least two reactor vessels are separated by a hydrophobic surface.
  • the hydrophilic surface is formed on an upper surface of the pillar and defines the lateral boundary of the least one reactor vessel.
  • the at least one reactor vessel is a well having a depth extending below a plane of the substrate that is defined by one or more sidewalls and a base, wherein one or more hydrophilic surfaces are formed on the base.
  • the platform described herein may include that the at least one reactor vessel is a hydrophilic surface positioned on the plane of the substrate and a hydrophobic surface positioned on the plane of the substrate that surrounds the hydrophilic surface.
  • the methods and systems described herein can rapidly and efficiently provide protein identification of each of the proteins from a proteome or a complement of proteins obtained from extremely small amounts of biological samples.
  • the identified proteins can be imaged quantitatively over a spatial region.
  • Automation and robotics facilitates the throughput of the methods and systems, which enables proteome analysis and imaging.
  • the small sample size poses a challenge to automation that is overcome by the embodiments described herein.
  • dilution of a processed sample with buffer yields a diluted sample having sufficient volume to be handled by a MS-based analytical instrument autosampler. Unexpectedly, the dilution of the processed sample still yields sufficient signal-to-noise ratio for analysis.
  • a method of proteome analysis comprises the steps of extracting from one NanoPOTS reactor vessel, a processed sample comprising less than 500 ng of a complement of proteins, peptides related to the complement of proteins, or both in a liquid buffer solution.
  • the NanoPOTS reactor vessel can be one of a plurality of vessels on a NanoPOTS plate.
  • the method can further comprise dispensing the processed sample into one well on a well plate having a plurality of wells, wherein the one well is pre-loaded with a volume of a liquid carrier buffer.
  • the volume of the liquid carrier buffer is a non- zero amount that is less than 50 pL, 35 pL, 25 pL, or 15 pL.
  • the processed sample can be diluted, thereby yielding in the one well a diluted sample.
  • the diluted sample is then transferred from the one well to a mass- spectrometry-based (MS-based) analytical instrument.
  • MS-based analytical instruments can include, but are not limited to, electrospray ionization-MS (ESI-MS), liquid chromatography- electrospray ionization-MS (LC-ESI-MS), capillary electrophoresis- electrospray ionization-MS (CE-ESI-MS), electrospray ionization-ion mobility spectrometry-MS (ESI-IMS- MS), and solid-phase extraction-ESI-MS (SPE-ESI-MS).
  • ESI-MS electrospray ionization-MS
  • LC-ESI-MS liquid chromatography- electrospray ionization-MS
  • CE-ESI-MS capillary electrophoresis- electrospray ionization-MS
  • the complement of proteins comprises at least 1000 proteins.
  • the complement of proteins can comprise at least 2000 proteins.
  • Embodiments can further comprise the step of co-registering a spatial region of a biological sample with a NanoPOTS reactor vessel, and with a well.
  • the spatial region has dimensions less than or equal to 500 pm. In further embodiments, the spatial region has dimensions less than or equal to 100 pm.
  • liquid carrier buffers can include, but are not limited to phosphate-buffered saline, ammonium bicarbonate, tris(hydroxymethyl)aminomethane, liquid chromatography mobile phase, and combinations thereof.
  • the liquid carrier buffer contains an MS- compatible surfactant.
  • MS-compatible surfactant can include, but are not limited to, ProteaseMAX, RapiGest, PPS Silent Surfactant, oxtyl b-D-glucopyranoside, n-dodecyl b-D- maltoside (DDM), digitonin, Span 80, Span 20, sodium deoxycholate, or a combination thereof.
  • methods can further comprise the step of providing protein identification for each of a plurality of proteins composing the complement of proteins.
  • the methods and systems can provide a quantification of the protein amount for each protein identification. For example, a mass spectrum is generated for each diluted sample.
  • a MS intensity value exists for every identified protein in each diluted sample.
  • the intensity value can be correlated with a quantity based on a calibration in order to yield a quantification of the identified protein.
  • the plurality of proteins can comprise at least 1000 proteins.
  • the plurality of proteins comprises at least 2000 proteins.
  • methods can further comprise generating a visual representation of the protein identifications.
  • the visual representation comprises one or more of the protein identifications mapped to a spatial region of a tissue sample.
  • protein identifications refer to identifications based on accurate mass and retention time, or ion fragments by matching to protein sequence database.
  • the diluted sample volume can be at least 5 qL to enable handling by an autosampler associated with a MS-based analytical instrument. If the volume is too small, the autosampler is incapable of transfer.
  • the diluting step further comprises dispensing a volume of a wash solution into the one reactor vessel and subsequently transferring the one reactor vessel’s contents to the one well. In further embodiments, said steps of dispensing a volume of a wash solution and said transferring the one reactor vessel’s contents are repeated at least once.
  • said transferring the diluted sample from the one well to a MS- based analytical instrument comprises contacting the well plate with a notched tip of a syringe, extracting the diluted sample from the one well into the syringe, and dispensing into the MS-based analytical instrument via the syringe.
  • the notched syringe tip is in close proximity to the well plate but does not actually contact. Examples of distances between the notched syringe tip and the well plate include, but are not limited to, less than 0.5 mm, less than 0.1 mm, less than 0.05 mm, and less than 0.01 mm.
  • a proteome analysis system comprises a receiver for a nanoPOTS platform plate, the plate comprising a plurality of reactor vessels having a non-zero footprint area less than 25 mm 2 ; a receiver for a microwell plate comprising a plurality of microwells; a sample transfer sub-system comprising a transfer syringe; a motorized translation stage configured to position the transfer syringe and each of the reactor vessels in alignment to facilitate sample extraction from the reactor vessel and further configured to position the transfer syringe and each of the microwells in alignment to facilitate sample dispensing into the microwells; an autosampler comprising an autosampler syringe having a notched syringe tip, wherein the autosampler is configured to position the notched syringe tip in contact with a bottom surface of the microwell; and an MS-based analytical instrument receiving sample injections from the autosampler syringe.
  • Examples of transfer syringes can include, but are not limited to, microliter syringes and nanoliter syringes.
  • Examples of the volume of liquid that is transferred from the nanoPOTS plate to the microwell plate can include, but is not limited to, a non- zero amount that is less than 50 qL, 25 pL, or 15 pL.
  • systems can further comprise a data processing sub-system comprising processing circuitry configured to identify each of at least 250 proteins related to a proteome based on data from the MS-based analytical instrument. In some instances the sub-system is configured to identify each of at least 500, 1000, or 2000 proteins. In other embodiments, systems can further comprise a control sub-system operably connected to the motorized translation sub-system and the autosampler, the control sub-system comprising processing circuitry configured to maintain co-registration between a spatial region of a tissue sample, a processed sample in a reactor vessel, and a diluted sample in a microwell.
  • systems can further comprise a data processing sub-system comprising processing circuitry configured to identify each protein related to a proteome based on data from the MS-based analytical instrument, wherein the processing circuitry is further configured to generate a visual representation comprising a mapping of protein identifications to spatial regions of the tissue sample based on the co-registration. In some embodiments there are at least 250, 500, 1000, or 2000 proteins.
  • FIG. 1 is a schematic depicting an exemplary embodiment of an operating environment including a robotic platform configured to dispense biological samples and reagents into a chip containing one or more reactor vessels (e.g., nanovessel) for nanoscale sample preparation.
  • a robotic platform configured to dispense biological samples and reagents into a chip containing one or more reactor vessels (e.g., nanovessel) for nanoscale sample preparation.
  • reactor vessels e.g., nanovessel
  • FIG. 2 is a schematic of the chip of FIG. 1 including a substrate, a spacer, a sealing membrane, and a cover slide.
  • the cover slide can be reversibly secured to the spacer for dispensing and incubation
  • FIGS. 3A-3E are schematics depicting embodiments of procedures for fabrication and surface modification of a substrate of the chip of FIG 2.
  • FIG. 3A depicts a schematic of the fabrication and assembly of the chip, where the chip may be pre-coated with an anti-reflective coating (e.g., chromium) and photoresist.
  • FIG. 3B depicts a chip after etching the photomask.
  • an anti-reflective coating e.g., chromium
  • FIG. 3C depicts the chip after etching the anti-reflective coating and the substrate to form a patterned substrate.
  • FIG. 3D depicts the patterned substrate including the anti-reflective coating after removal of the photoresist.
  • FIG. 3E depicts the chip after removal of the anti-reflective coating, showing a pattern of pillars and wells.
  • FIGS. 4A-4B are diagrams illustrating exemplary embodiments of reactor vessels defined by the chip patterned substrate of the chip including pillars and wells formed there between.
  • FIG. 4A depicts one exemplary embodiment of the patterned substrate where the one or more reactor vessels is defined by the upper surfaces of the pillars.
  • the pillars can include hydrophilic upper surfaces and the wells can include hydrophobic upper surfaces.
  • FIG. 4B depicts another exemplary embodiment of the patterned substrate where the one or more reactor vessels is defined by the wells, between the pillars.
  • the hydrophilic surfaces can be provided by the bare surface of the substrate (e.g., glass surfaces) or hydrophilic coatings.
  • the hydrophobic surfaces can be provided by hydrophobic coatings.
  • FIG. 5 depicts another exemplary embodiment of a patterned chip substrate in a substantially planar configuration, where the reactor vessels are flush with the substrate surface and defined within first regions of the substrate having hydrophilic surfaces and bounded by adjacent second regions having hydrophobic surfaces.
  • FIG. 6 depicts a flow diagram illustrating one exemplary embodiment of a sample preparation protocol for the methods described herein including a biological sample treatment operation.
  • FIGS. 7-8 depict schematics of exemplary embodiments of the sample preparation of the methods described herein.
  • FIG. 7 depicts exemplary workflow of a sample, including, extraction/reduction, alkylation, Lys-C digestion, trypsin digestion, surfactant cleavage and peptide collection.
  • FIG. 8 depicts an exemplary workflow of a sample (e.g., cells) that are lysed, alkylated, digested - by Lys C and trypsin.
  • FIG. 9 illustrates an exemplary operating environment including a transfer vessel in the form of a capillary collecting a processed biological sample via aspiration from the nanowell chip.
  • FIG. 10 is a schematic of a capillary used to collect processed sample which can be readily connected to an analytical instrument, such as a mass spectrometer.
  • FIGS. 11A-11C depict preliminary proteomic results employing embodiments of the sample preparation method of FIG. 6.
  • FIG. 11A depicts a base peak chromatogram acquired from 160 cells; an embodiment of a nanowell with cells positioned therein is shown in the insert.
  • FIG. 11B is a bar graph depicting peptide spectral matches (PSMs), unique peptides and identified proteins from duplicate runs of the 160 cells.
  • FIG. 11C depicts a schematic showing the protein overlap from duplicate runs.
  • FIGS. 12A-12C are images depicting HeLa cells in nanowells.
  • FIG. 12A depicts 12 HeLa cells.
  • FIG. 12B depicts 42 HeLa cells.
  • FIG. 12C depicts 139 HeLa cells.
  • FIGS. 13A-13C are base chromatograms of the HeLa cells in nanowells corresponding to FIGS. 12A-12C, respectively.
  • FIGS. 14A-14B show the sensitivity and reproducibility of the nanoPOTS platform.
  • FIGS. 14A-14B are bar graphs depicting the number of unique peptides (FIG. 14A) and protein groups identified from different cell loadings (FIG. 14B).
  • FIG. 15 presents bar graphs depicting peptide and protein identification from three blank control samples including solid phase extraction (SPE) and liquid chromatography (LC) columns, sample preparation reagents, and cell supernatant.
  • buffer A e.g., storage buffer
  • PBS buffer instead of cells was dispensed into nanowells, followed by all proteomic processing steps, e.g., from FIGS. 5-7.
  • cell suspension with a concentration of -200 cell/pL was centrifuged at 2000 rpm for 10 min. The supernatant was dispensed into nanowells followed by all proteomic processing steps. All identification experiments were run after ⁇ l00-cell samples.
  • FIGS. 16A-16B are graphs depicting the distribution of copy number per cell for proteins identified from 10-14 HeLa cells by matching with previously-reported databases, containing 40 proteins obtained with PrEST-SILAC method (Tyanova et al.) (FIG. 16A), and 5443 proteins using the histone-based“proteomic ruler” method (FIG. 16B).
  • FIGS. 17A-17D are images depicting the label-free quantification (LFQ) reproducibility. Pairwise correlation of protein LFQ intensities, between, lO-cell and l2-cell samples (FIG. 17A), 37-cell and 42-cell samples (FIG. 17B), l37-cell and l4l-cell samples (FIG. 17C).
  • FIG. 17D depicts a violin plot showing the distributions of coefficients of variance of protein LFQ intensities for the three cell loading groups (10-12 cells, 37-41 cells, and 137-141 cells).
  • FIGS. 18A-18D depict box charts showing the distributions of (al FIG. 18A, bl FIG 18B) coefficients of variance and (a2 FIG 18C, b2 FIG. 18D) log intensities at (al, a2) peptide and (bl, b2) protein level for three cell loading groups.
  • Peptide intensities were normalized based on global normalization approach in each cell loading group.
  • LFQ intensities generated by Maxquant were used for protein quantification.
  • FIG. 19 depicts a schematic showing the workflow of the isolation of laser microdissected of human pancreatic islets into nanowells.
  • FIG. 20A depicts images showing the pairwise correlation analysis of protein expression level in nine human islet slices.
  • FIG. 20B depicts images of the nine islet sections used as described herein.
  • FIG. 21 depicts an image showing the protein coverage of a network involved in vesicular transport.
  • FIG. 22 depicts a bar graph depicting the evaluation of trypsin digestion efficiency.
  • FIGS. 23A-23D depicts images of (a-b) overlap of identified protein groups from three cell loading groups with (FIG. 23A) MS/MS only method, and (FIG. 23B) combined MS/MS and MBR method.
  • FIGS. 23C-23D Overlap of protein groups identified from similar cell loadings of 10, 12, and 14 cells with (FIG. 23C) MS/MS only method, and (FIG. 23D) combined MS/MS and MBR method.
  • FIGS. 24A-24C are bar graphs depicting the quantifiable numbers of (FIG. 24A) peptide numbers and (FIG. 24B and FIG. 24C) protein group numbers for three cell loading groups. Peptides and proteins having intensities in all 3 samples with similar cell numbers were counted as quantifiable identifications.
  • FIGS. 25A-25C depicts a pairwise correlation analysis of any two samples in peptide intensity level with cell loadings groups of (FIG. 25A) 10-14 cells, (FIG. 25B) 37 45 cells, and (FIG. 25C) 137-141 cells.
  • FIGS. 26A-26C depicts a pairwise correlation analysis of any two samples in protein intensity level with cell loadings groups of (FIG. 26A) 10-14 cells, (FIG. 26B) 37 45 cells, and (FIG. 26C) 137-141 cells. LFQ intensity generated from Maxquant was used for protein intensity calculation.
  • FIG. 27 is a bar graph depicting the comparison of Gene Ontology annotations for Cellular Component showing the protein identified from nanoPOTS and SNaPP platforms (Sun, L. et al.).
  • nanoPOTS platform datasets were generated 9 slices of LCM islets.
  • SNaPP platform datasets were generated from triplicate runs of more than 100 islets.
  • FIG. 28 depicts a graph showing the number of proteins identified versus the number of mammalian cells for previously published platforms (blue) and the present platform (red), indicating that the present platform has achieved greater proteome coverage from just 10-14 cells than was achieved previously from much larger samples.
  • FIGS. 29A-29E (FIG. 29A) Schematic diagram showing the direct integration of laser capture microdissection (LCM) with a nanowell chip using dimethyl sulfoxide (DMSO) droplets for tissue capture.
  • FIG. 29B Image of a nanowell chip with an array of 200-nL pre-populated DMSO droplets.
  • FIG. 29C Direct mounting of a nanowell chip on a slide adapter for a PALM microbeam LCM system.
  • FIG. 29D Microdissected tissue section and (FIG. 29E) the corresponding tissue pieces collected in nanowells with square side lengths from 20 pm to 200 pm. A l2-pm-thick breast cancer tissue was used as a model sample.
  • FIGS. 30A-30B Comparison of evaporation time of water and DMSO droplets with different volumes. Each condition was measured with five replicates.
  • FIG. 30B Evaluation of the capture efficiency of LCM tissue samples using DMSO droplets. A breast tissue section (12 pm thick) was used as a model sample. The replicates were 75, 75, 75, and 27 for the tissues having side lengths of 20 pm, 50 pm, 100 pm, and 200 pm, respectively. 200 nL DMSO droplets pre deposited in nanowells with a diameter of 1.2 mm were used for tissue collection.
  • FIGS. 31A-31G Unique peptides (FIG. 31A) and protein identifications (FIG. 31B) of rat brain cortex tissue samples obtained with laser capture microdissection followed by DMSO and DMSO-free-based sample collection methods.
  • FIG. 31C Venn diagram of the total protein identifications. Tissue size: 200 mhi in diameter and 12 mhi in depth.
  • FIGS. 31D-31F Evaluation of the sensitivity of the LCM-DMSO-nanoPOTS system in proteomic analysis of small rat cortex tissue samples. The relationship of tissue sizes with unique peptides (FIG. 31D) and protein (FIG. 31E) identifications, and (FIG.
  • FIG. 31F GOCC analysis of the 1918 proteins identified from 200-pm cortex tissues using an online tool DAVID. All peptide and protein identifications were based on MS/MS spectra (Match Between Runs was disabled). Each condition was analyzed in triplicate.
  • FIGS. 32A-32C The rat brain coronal section (12 pm thick) used in the study. Three distinct regions including cerebral cortex (CTX), corpus callosum (CC), and caudoputamen (CP) were dissected with a spatial resolution of 100 pm in diameter.
  • CTX cerebral cortex
  • CC corpus callosum
  • CP caudoputamen
  • FIG. 32B The corresponding microscopic images of the tissue regions after dissection.
  • FIG. 32C Pair wise correlation plots with log2-transformed LFQ intensities between total 12 tissue samples from the three regions. The color codes indicate the relatively high correlations between the same tissue regions and relatively low correlations between different regions.
  • FIGS. 33A-33B Principle component analysis (PCA) of protein expressions in CTX, CC, and CP regions of rat brain section as shown in FIGS. 32A-32C.
  • PCA Principle component analysis
  • HCA Hierarchical clustering analysis
  • FIG. 34A depicts a top front view of a chip showing droplets hanging from the individual reactor vessels during incubation.
  • FIG. 34B depicts a side view of a chip showing droplets hanging from the individual reactor vessels during incubation.
  • FIG. 35 depicts various aspects of methods and systems for automated proteome analysis according to embodiments described herein.
  • FIGS. 36A and 36B are different perspective views of a notched syringe tip.
  • FIG. 37 depicts co-registration of a spatial region of a biological sample with a nanoPOTS reactor vessel and a well-plate well, which facilitates proteome mapping.
  • Embodiments of the present disclosure relate to systems and methods for preparation and analytical analysis of biological samples. More particularly, embodiments of the present disclosure relate to preparation and analysis of biological samples having nanoscale volumes, interchangeably referred to herein as nanoPOTS: Nanowell-based Preparation in One-pot for Trace Samples. As discussed in detail below, increased efficiency and recovery of proteomic sample processing by downscaling total preparation volumes to the nanoliter range (e.g., from the range of about 100 pL to about less than 5 pL).
  • NanoPOTS proteomic sample preparation and analysis for small cell populations can be improved, for example by reducing the total processing volume to the nanoliter range within a single reactor vessel.
  • the present platform, NanoPOTS can enable each sample to be processed within a 200 nL or smaller droplet that is contained in a wall-less glass reactor having a diameter of approximately 1 mm (e.g., total surface area of about 0.8 mm 2 ).
  • a 100 pL typical sample preparation volume in 0.5 mL-centrifuge tubes (127.4 mm 2 ) the surface area was reduced by a factor of -160, greatly reducing adsorptive losses.
  • NanoPOTS When combined with analysis by ultrasensitive liquid chromatography-mass spectroscopy (LC-MS), biological samples prepared using nanoPOTS can enable deep profiling of greater than about 3000 proteins from as few as about 10 HeLa cells, a level of proteome coverage that has not been previously achieved for fewer than 10,000 mammalian cells.
  • NanoPOTS can enable robust, quantitative and reproducible analyses and provide in-depth characterization of tissue substructures by profiling thin sections of single human islets isolated from clinical pancreatic specimens.
  • FC and MC are also inherently targeted techniques with limited multiplexing capacity.
  • MS mass spectrometry
  • Efforts to improve sample preparation procedures include the use of low-binding sample tubes and‘one pot’ digestion protocols to limit total surface exposure (Sun, X, et al., Wisniewski, J et al, Chen, Q et al, Chen W. et al, Waanders, L. et al, Huang, E. et al, and Wang, N. et al).
  • Ultrast, X, et al., Wisniewski, J et al, Chen, Q et al, Chen W. et al, Waanders, L. et al, Huang, E. et al, and Wang, N. et al trifluoroethanol-based protein extraction and denaturation
  • filter-aided sample preparation 13 MS-friendly surfactants (Waanders, L.
  • Samples employed in embodiments of the systems and methods described herein may be any liquid, semi-solid or solid substance (or material).
  • a sample can be a biological sample or a sample obtained from a biological material.
  • a biological sample can be any solid or fluid sample obtained from, excreted by or secreted by any living organism, including without limitation, single celled organisms, such as bacteria, yeast, protozoans, and amoebas among others, multicellular organisms (such as plants or animals, including samples from a healthy or apparently healthy human subject or a human patient affected by a condition or disease to be diagnosed or investigated, such as cancer).
  • a biological sample can be a biological fluid obtained from, for example, blood, plasma, serum, urine, bile, ascites, saliva, cerebrospinal fluid, aqueous or vitreous humor, or any bodily secretion, a transudate, an exudate (for example, fluid obtained from an abscess or any other site of infection or inflammation), or fluid obtained from a joint (for example, a normal joint or a joint affected by disease).
  • a biological sample can also be a sample obtained from any organ or tissue (including a biopsy or autopsy specimen, such as a tumor biopsy) or can include a cell (whether a primary cell or cultured cell) or medium conditioned by any cell, tissue or organ.
  • a biological sample can be a nuclear extract.
  • a biological sample can be bacterial cytoplasm.
  • a sample can be a test sample.
  • a test sample can be a cell, a tissue or cell pellet section prepared from a biological sample obtained from a subject.
  • the subject can be one that is at risk or has acquired a particular condition or disease.
  • the sample can be cells isolated from whole blood or cell isolated from histological thin sections.
  • Illustrative biological samples include nanoscale biological samples (e.g., containing low- or subnanogram (e.g., less than about 1 ng) amounts of protein which may be processed in a single nanowell or subdivided into multiple nanowells).
  • the biological sample is a tissue
  • the tissue may be fixed.
  • Tissues may be fixed by either perfusion with or submersion in a fixative, such as an aldehyde (such as formaldehyde, paraformaldehyde, glutaraldehyde, and the like).
  • a fixative such as an aldehyde (such as formaldehyde, paraformaldehyde, glutaraldehyde, and the like).
  • fixatives include oxidizing agents (for example, metallic ions and complexes, such as osmium tetroxide and chromic acid), protein-denaturing agents (for example, acetic acid, methanol, and ethanol), fixatives of unknown mechanism (for example, mercuric chloride, acetone, and picric acid), combination reagents (for example, Camoy’s fixative, methacarn, Bouin’s fluid, B5 fixative, Rossman’s fluid, and Gendre’s fluid), microwaves, and miscellaneous (for example, excluded volume fixation and vapor fixation).
  • Additives also may be included in the fixative, such as buffers, detergents, tannic acid, phenol, metal salts (for example, zinc chloride, zinc sulfate, and lithium salts), and lanthanum.
  • the method for preparing a biological sample may include displacing a volume of biological sample to a single reactor vessel.
  • the volume of biological sample can be a non-zero amount less than 5 pL.
  • the volume of biological sample may a non-zero amount less than about 4 pL, less than about 3 pL, less than about 2 pL, less than about 1 pL, less than about 500 nL, less than about 400 nL, less than about 300 nL, less than about 200 nL, less than about 190 nL, less than about 180 nL, less than about 170 nL, less than about 160 nL, less than about 150 nL less than about 140 nL, less than about 130 nL, less than about 120 nL, less than about 110 nL, less than about 100 nL, less than about 90 nL, less than about 80 nL, less than about 70 nL, less than about 60 n
  • the biological sample comprises about 50 nL.
  • the biological sample e.g., cultured cells or non-cultured cells
  • Confluency refers to cells in contact with one another on a surface (e.g., a tissue culture vessel, a petri dish, a well, and the like).
  • a surface e.g., a tissue culture vessel, a petri dish, a well, and the like.
  • it can be expressed as an estimated (or counted) percentage, e.g., 10% confluency means that 10% of the surface, e.g., of a tissue culture vessel, is covered with cells, 100% means that it is entirely covered.
  • adherent cells grow two dimensionally on the surface of a tissue culture well, plate or flask.
  • Non-adherent cells can be spun down, pulled down by a vacuum, or tissue culture medium aspiration off the top of the cell population, or removed by aspiration or vacuum removal from the bottom of the vessel.
  • the biological sample may include HeLa cells, A549 cells, CHO cells or MCF7 cells, K562 cells, or THP-l cells, microbial cells, plant cells, or virtually any other biological material.
  • the biological sample may include of primary or immortalized cells.
  • primary or immortalized cells include but are not limited to, mesenchymal stem cells, lung cells, neuronal cells, fibroblasts, human umbilical vein (HUVEC) cells, and human embryonic kidney (HEK) cells, primary or immortalized hematopoietic stem cell (HSC), T cells, natural killer (NK) cells, cytokine- induced killer (CIK) cells, human cord blood CD34+ cells, B cells.
  • T cells may include CD8+ or CD4+ T cells.
  • the CD8+ subpopulation of the CD3+ T cells are used.
  • CD8+ T cells may be purified from the PBMC population by positive isolation using anti-CD8 beads.
  • the biological sample may include tissues, including but not limited, liver tissue, brain tissue, pancreatic tissue, breast cancer tissue, or plant tissue.
  • the biological sample is collected and prepared using standard techniques.
  • cultured cells are collected and centrifuged. The pellet is then washed and re-suspended.
  • the suspended cells are concentration to obtain desired cell numbers.
  • the desired number of cells can be readily optimized.
  • the number of cells is 1 cell, 2 cells, 3 cells, 4 cells, 5 cells, 6 cells, 7 cells, 8 cells, 9 cells, 10 cells, 15 cells, 20 cells, 30 cells, 40 cells, 50 cells, 100 cells, 200 cells.
  • the sample is then adjusted to obtain a nano liter cell suspension (e.g., a 50 nL cell suspension).
  • the biological sample is a laser microdissected tissue, wherein the tissue is less than about 1000 pm, less than about 900 pm, less than about 800 pm, less than about 700 pm, less than about 600 pm, less than about 500 pm, less than about 400 pm, less than about 300 pm, less than about 200 pm, less than about 100 pm, less than about 50 pm, less than about 40 pm, less than about 30 pm, less than about 20 pm, less than about 10 pm, less than about 5 pm.
  • a robotic nanoliter dispensing platform 100 can be employed to perform sample processing steps associated with bottom-up proteomics (e.g., robotic platform (Vandermarlier, E et al)).
  • dispensing platform 100 can include a translatable stage 102 configured to receive a chip 104.
  • the chip 104 can be configured to retain biological samples and reagents dispensed therein for further processing.
  • the robotic platform 100 can be configured to provide submicron positioning accuracy and capacity for accurately handling picoliter volumes to dispense cells and reagents into reactor vessels formed in the chip 104 for further processing (e.g., to yield a processed sample). and to retrieve samples for subsequent analysis.
  • Biological samples and/or reagents can be dispensed in the chip 104 via a syringe pump 206 including a picoliter dispensing tip 110 under the control of a controller, which can include one or more user interfaces for receiving commands from a user.
  • the syringe pump 106 can be in fluid communication with a source of the biological samples (not shown) and one or more reservoirs 114 containing reagents.
  • the platform 100 can further include a camera 116 or other imaging device for viewing dispensing of the biological samples and/or reagents.
  • the total volume of biological samples and/or reagents can be less than 200 nL (in particular embodiments, a non-zero amount of less than 200 nL).
  • Embodiments of the method can dramatically reduce surface contact to minimize sample loss while also enhancing reaction kinetics.
  • the nanoPOTS platform described herein can reduce the total processing volumes (for example, the volume of the biological sample plus the total volume of all the reagents for processing) from the conventional tens or hundreds of microliters to less than 5,000 nL, less than 3,000 nL, less than 2,000 nL, less than 1,000 nL, less than 500 nL, less than 400 nL, less than 300 nL, less than 200 nL, less than 100 nL, less than 50 nL, less than 20 nL, less than 10 nL, less than 5nL.
  • the total processing volumes for example, the volume of the biological sample plus the total volume of all the reagents for processing
  • the biological sample may be processed in a single reactor vessel to yield a processed sample.
  • the single reactor vessel avoids the need to transfer samples to multiple reactor vessels for processing and therefore avoids the corresponding sample losses that such steps incur.
  • the biological sample is processed in a single reactor vessel, a cocktail containing a reducing agent (e.g., dithiothreitol) is added and the sample is incubated.
  • a cocktail containing a reducing agent e.g., dithiothreitol
  • the pH is between 5 and 10, preferably 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5 or 10. More preferably, a solution pH value of 8 may be used.
  • a protease is then added to the single reactor vessel (e.g., trypsin or LysC).
  • the addition of a protease allows digestion of the polypeptides.
  • the process may be performed in a humidity-controlled chamber.
  • the humidity-controlled chamber is maintained at a relative humidity within the range from about 80% to about 100%, e.g., at about 95% humidity.
  • a cover plate may be employed to minimize evaporation.
  • the single reactor vessel is sealed during incubation times (e.g., after the addition of a reducing agent).
  • the sealed single reactor vessel aids in minimizing evaporation and therefore sample loss.
  • methods disclosed herein may include steps such as washing steps to maximize recovery (e.g., into a capillary).
  • the capillary can be fused or sealed from the external environment and stored.
  • the processed biological sample is washed with a buffer (e.g., with water containing formic acid), and in some examples, multiple washing steps are performed, for example, 2 washing steps.
  • Storage of the processed biological sample in the capillary may be short term (e.g., at about -20°C for less than 6 months) or long term (e.g., at about -70°C for greater than 12 months).
  • the chip can be inverted during sample incubation to prevent the sample from settling on the reactor vessel surface (see FIGS. 34A and 34B).
  • droplets containing the biological sample may hang below the reactor vessel surface.
  • the processed biological sample can be subjected to mass spectrometry for identification, characterization, quantification, purification, concentration and/or separation of polypeptides without further steps of sample preparation. Since embodiments of the disclosed sample preparation methods can be performed in a single reactor vessel without filtering, precipitation or resolubilization steps, it can facilitate efficient analysis of cell-limited samples.
  • Embodiments of the disclosed systems and methods, as described herein, can have broad application in the fields of proteomics, metabolomics, and lipidomics, as such robust analysis from small samples have not been achievable using previously developed procedures.
  • this description of potential applications is non- limiting and one skilled in the art will appreciate that embodiments of the disclosure can be employed in other applications without limit.
  • biological samples processed according to embodiments of the disclosed systems and methods may be analyzed using a variety of methods.
  • the methods used to analyze the processed biological sample can include, but are not limited to, quantitative proteomic analysis methods.
  • the processed biological sample may be analyzed mass spectrometry.
  • Mass spectrometry can utilize matrix-assisted laser desorption/ionization (MALDI), electrospray ionization (ESI), and other specialized mass spectrometry techniques.
  • MALDI mass spectrometry is a technique for the analysis of peptide mixtures resulting from proteolysis (e.g., digestion of proteins by trypsin).
  • proteolysis e.g., digestion of proteins by trypsin.
  • Embodiments of the methods disclosed herein can be used for top-down or bottom-up proteomics.
  • Chromatography can also be employed for peptide separation.
  • Liquid chromatography or capillary electrophoresis can be coupled to mass spectrometry, particularly with an electrospray ionization source.
  • a transfer device e.g., a transfer capillary
  • the microextraction column can, in turn, be coupled to the head of the liquid chromatography column.
  • the transfer capillary may also be directly coupled to the head of the liquid chromatography column.
  • the analyzing the processed biological sample can identify unique species, including but not limited to proteins or fragments thereof, lipids, or metabolites.
  • analyzing the processed biological sample can identify at least about 1,000 unique species (e.g., proteins or fragments thereof, lipids, and/or metabolites). In additional embodiments, the processed biological sample can identify at least 2,000 unique species, at least 3,000 unique species, at least 4,000 unique species, at least 5,000 unique species, at least 7,000 unique species. In other embodiments, the number of unique species identified can be at least 500 or more proteins and/or 100 or more metabolites or lipids.
  • the methods described herein can allow for the identification and quantitative measurements from less than about 200 cells (e.g., from the range of about 1 to about 50 mammalian cells).
  • method described herein enables for
  • nanowell sample processing can be coupled with laser-capture microdissection (LCM) for deep proteome analysis of heterogeneous tissue thin sections with ⁇ 100 pm resolution. Deciphering the cellular interactions that drive disease within tissue
  • microenvironment can be beneficial for understanding tumor formation and propagation, developing drug targets, and designing personalized treatment regimens.
  • LCM can differentiate and isolate subsections of tissue with high specificity
  • sample requirements for proteomics can limit the resolution of LCM to large or pooled thin sections comprising thousands or tens of thousands of cells and millimeter or larger dimensions.
  • Such heterogeneous tissues can confound molecular analysis due to a blurring of cellular constituents and their respective contributions.
  • embodiments of the presently disclosed systems and methods can provide proteomic analysis of LCM-isolated tissues by reducing sample size by approximately 2 orders of magnitude, to less than about 50 cells, which can enable both high resolution proteomic imaging (e.g., less than about 100 pm) as well as isolation of specific tissues from much smaller samples, such as smears from fine needle aspiration biopsies.
  • LCM can be used to excise and transfer select tissue from thin section to embodiments of the nanowell.
  • an LCM e.g., Zeiss PALM Microbeam LCM ®
  • FFPE paraffin embedded
  • the Zeiss system can provide submicron resolution and it can be equipped with laser-pressure catapulting to eject excised samples to a variety of substrates, including centrifuge tube lids and slides (e.g., 25 x 75 mm).
  • the Zeiss LCM can be compatible with standard glass slides for archived specimens as well as LCM-dedicated polymer membrane-coated slides.
  • Embodiments of the nano wells can be configured for compatibility with the 25 x 75 mm form factor. This can allow for direct coupling and facilitate transfer from thin sections to the nanowells. As discussed in greater detail below, the nanowells can have a diameter of about 0.5 mm to about 1.5 mm. The spacing between the nano well slide and the thin section slide may be adjusted to achieve the requisite transfer accuracy. Nanowell surface treatments may be implemented as needed to ensure adhesion of the catapulted tissue upon contact. As an alternative approach, excised samples can be catapulted into centrifuge tube caps and micromanipulation- based strategies can be used to transfer the sample to the nanowell.
  • sample processing can be seamlessly integrated with LCM by providing a capture liquid in or on a reactor vessel.
  • This method can avoid manual transfer of dissected tissues to the nanowells that is required in a conventional LCM system.
  • tissue pieces may be collected into microtubes by gravity or catapulted into tube caps prefilled with extraction solution or adhesive coating, depending on the instrument vendor and configuration.
  • these collection approaches cannot be
  • the capture liquid may have an ultra- low vapor pressure (for example, less than or equal to 0.8 mbar at room temperature), and evaporates very slowly under ambient conditions, which allows for long working times and uninterrupted sample collection.
  • the evaporation times of 100 nL to 300 nL dimethyl sulfoxide (DMSO) droplets were 194 min to 416 min, which were >50 times longer than for water droplets. Such prolonged times are sufficient to collect up to hundreds of tissue samples in each chip.
  • DMSO dimethyl sulfoxide
  • the capture liquid can be completely removed by gentle heating or vacuum, eliminating any possible interference during subsequent sample processing and analysis steps.
  • the capture liquid Compared with other low- vapor-pressure solvents such as dimethylformamide, the capture liquid should have a lower toxicity, thus enabling its use as a storage solvent for cells.
  • An illustrative capture liquid is dimethyl sulfoxide (DMSO).
  • DMSO dimethyl sulfoxide
  • the freezing point of DMSO is 18.5 °C, which should facilitate chip and sample transfer between histology and analytical labs without the risk of sample mixing or losses during shipping.
  • DMSO significantly increases the sensitivity of protein identification of brain tissues, which may be ascribed to improved protein extraction efficiency as explained in more detail below.
  • the amount of capture liquid provided in each nanowell may be sufficient to cover a portion of, or the entire surface, of the nanowell.
  • the capture liquid may be present in an amount of at least 1 nL to 1000 nL.
  • Embodiments of the methods described herein can be used for molecular characterization of tissue cellular heterogeneity or pathology in a variety of diseases.
  • Exemplary diseases can include, but are not limited to, inflammatory diseases, metabolic diseases, cancers, neoplasias, and the like.
  • metabolic disease can include its customary and ordinary meaning and can refer to diabetes, including type II diabetes, insulin-deficiency, insulin-resistance, insulin- resistance related disorders, glucose intolerance, syndrome X, inflammatory and immune disorders, osteoarthritis, dyslipidemia, metabolic syndrome, non-alcoholic fatty liver, abnormal lipid metabolism, neurodegenerative disorders, sleep apnea, hypertension, high cholesterol, atherogenic dyslipidemia, hyperlipidemic conditions such as atherosclerosis, hypercholesterolemia, and other coronary artery diseases in mammals, and other disorders of metabolism.
  • the methods as used herein can be used in characterizing type 1 or type 2 diabetes.
  • neoplasia can include its customary and ordinary meaning and can refer to a disease or disorder characterized by excess proliferation or reduced apoptosis.
  • Illustrative neoplasms for which the embodiment may be used include, but are not limited to pancreatic cancer, leukemias (e.g., acute leukemia, acute lymphocytic leukemia, acute myelocytic leukemia, acute myeloblastic leukemia, acute promyelocytic leukemia, acute myelomonocytic leukemia, acute monocytic leukemia, acute erythroleukemia, chronic leukemia, chronic myelocytic leukemia, chronic lymphocytic leukemia), polycythemia vera, lymphoma (Hodgkin's disease, non-Hodgkin's disease), Waldenstrom's macroglobulinemia, heavy chain disease, and solid tumors such as sarcomas and carcinomas (e.g.,
  • biological sample can include its customary and ordinary meaning and can refers to a sample obtained from a biological subject, including sample of biological tissue or fluid origin obtained in vivo or in vitro.
  • samples can be, but are not limited to, body fluid (e.g., blood, blood plasma, serum, or urine), organs, tissues, fractions, and cells isolated from mammals including, humans.
  • Biological samples also may include sections of the biological sample including tissues (e.g., sectional portions of an organ or tissue).
  • Biological samples may also include extracts from a biological sample, for example, an antigen from a biological fluid (e.g., blood or urine).
  • a biological sample may be of prokaryotic origin or eukaryotic origin (e.g., insects, protozoa, birds, fish, or reptiles).
  • the biological sample can be mammalian (e.g., rat, mouse, cow, dog, donkey, guinea pig, or rabbit).
  • the biological sample can be of primate origin (e.g., example, chimpanzee, or human).
  • transitional term “comprising,” which is synonymous with “including,” “containing,” or “characterized by,” is inclusive or open-ended and does not exclude additional, unrecited elements or method steps.
  • the transitional phrase “consisting of’ excludes any element, step, or ingredient not specified in the claim.
  • the transitional phrase “consisting essentially of’ limits the scope of a claim to the specified materials or steps "and those that do not materially affect the basic and novel characteristic(s)" of the claimed embodiments.
  • “Detectable moiety” or a“label” can include its customary and ordinary meaning and it can refer to a composition detectable by spectroscopic, photochemical, biochemical,
  • useful labels include 32 P, 35 S, fluorescent dyes, electron-dense reagents, enzymes (e.g. , as commonly used in an ELISA), biotin-streptavidin, dioxigenin, haptens and proteins for which antisera or monoclonal antibodies are available, or nucleic acid molecules with a sequence complementary to a target.
  • the detectable moiety can generate a measurable signal, such as a radioactive, chromogenic, or fluorescent signal, that can be used to quantify the amount of bound detectable moiety in a sample. Quantitation of the signal can be achieved by, e.g., scintillation counting, densitometry, mass spectrometry, and/or flow cytometry.
  • FFPE formalin fixed paraffin embedded tissue
  • FFPE samples can be derived from tissues (often suspected tumor samples) that are fixed with formalin to preserve structural- spatial and biomolecule characteristics (e.g., cytoskeletal and protein structure) and then embedded in a type of paraffin wax so the tissue can be sliced.
  • Formalin can irreversibly cross-link proteins via the amino groups, thus preserving the structural integrity of the cells so they can be stained with dyes or with immunostains used to analyze for abnormalities in the tissue that indicate altered cellular conditions, e.g., cancer.
  • samples may be prepared using non-formalin reagents, including, for example, glutaraldehyde, mercurial, oxidizing agents, alcohols, and picrates.
  • hydrophilic surface can include its customary and ordinary meaning and it can refer to a surface to have native hydrophilic property such as glass or fused silica, or which either hydrophilic compounds are covalently or non-covalently attached or which is formed of a polymer that has hydrophilic properties.
  • the polymer with hydrophilic properties can be an organic polymer, (e.g., polyacrylamide, polyacrylic acid, polyacrylimide, polyelectrolytes, polyethylenimin, polyethylenglycol, polyethylenoxid, polyvinylalcohol, polyvinylpyrrolidon polystyrenesulfonic acid, copolymers of styrene and maleic acid, vinyl methyl ether malic acid copolymer, and polyvinylsulfonic acid.
  • organic polymer e.g., polyacrylamide, polyacrylic acid, polyacrylimide, polyelectrolytes, polyethylenimin, polyethylenglycol, polyethylenoxid, polyvinylalcohol, polyvinylpyrrolidon polystyrenesulfonic acid, copolymers of styrene and maleic acid, vinyl methyl ether malic acid copolymer, and polyvinylsulfonic
  • FIG. 2 An exemplary embodiment of a nanoPOTS chip, also referred to as a platform or chip 200, is illustrated in FIG. 2.
  • the chip 200 can include a substrate 202, a spacer 204, one or more sealing membrane 206, and a cover 210.
  • the spacer 204 can overlie the substrate 202
  • the sealing membrane 206 can overlie the spacer 204
  • the cover 210 can overlie the sealing membrane 206.
  • the substrate 202, the spacer 204, and the cover 210 can be formed from a material that is transparent to optical light (e.g., glass). Forming the substrate 202 from glass can facilitate microscopic imaging of samples and minimize protein and peptide adsorption relative to many other materials due to its hydrophilicity and reduced surface charge at low pH (Zhu, Y, et al.).
  • the substrate 202 can include a physical and/or chemical pattern 212 that defines at least one reactor vessel having one or more hydrophilic and/or hydrophobic surfaces configured for containment of a biological sample.
  • the hydrophilic surfaces can have a non-zero total surface area less than 5 mm 2 .
  • the spacer 204 can contain a first aperture 204a and the sealing membrane 206 can include a second aperture 206a.
  • the first and second apertures 204a, 206a can be dimensioned to accommodate the pattern 212 of reactor vessels when the chip 200 is assembled.
  • at least the first aperture 204a of the spacer can surround the pattern 212 of reactor vessels.
  • the sealing membrane 206 can be interposed between the spacer 204 and the cover 210 and it can be configured to form a fluid-tight seal between the spacer 204 and the cover 210.
  • the sealing membrane can be interposed between the substrate and the spacer. Formation of fluid-tight seals using the sealing membrane can minimize evaporation of reactor vessel contents when performing incubation during sample preparation, as discussed below.
  • other sealing mechanisms can be employed and the sealing membrane can be omitted.
  • the cover 210 can be pre-coated with a layer of sealing membrane such as PDMS (polydimethylsiloxane).
  • FIGS. 3A-3E illustrate an exemplary embodiment of forming the pattern 212 by photolithography.
  • a substrate 300 coated with an anti-reflective coating 302 and photoresist 304 is illustrated.
  • a photomask 306 can be used in conjunction with light 310 (e.g., ultraviolet light) to transfer a geometric pattern of the photomask 306 to the photoresist 304.
  • the anti-reflective coating 302 can be configured to control reflection and absorption of the light 310.
  • the portions of the photomask 306 and anti-reflective coating 302 outside the transferred pattern can be removed by a chemical etching to yield a patterned substrate 312 that includes pillars 314 defining wells 316 therebetween of predetermined depth within the substrate 300.
  • the photomask 306 and anti-reflective coating 302 remaining on the upper surface of the pillars 312 are removed with further chemical etching, as shown in FIGS. 3D-3E.
  • FIGS. 4A-4B illustrate embodiments of the patterned substrate 412 defining reactor vessels configured for multiple-step proteomic sample processing.
  • a hydrophobic coating can be deposited on the patterned substrate 412, adjacent to the pillars 414, to form a hydrophobic surface 402.
  • a hydrophilic coating can be deposited on the patterned substrate 412 on the upper surface of the pillars 414 to form a hydrophilic surface 404.
  • a hydrophobic coating can be omitted and the bare surface of the substrate can form the hydrophilic surface 404. So configured, the upper surface of each pillar 414 with the hydrophilic surface 404 can define the lateral boundary of respective reactor vessels 400.
  • the patterned pillars 414 can reduce surface area contact relative to the use of concave wells.
  • the locations of the hydrophobic and hydrophilic coatings can be reversed. That is, the hydrophilic coating can be deposited on the patterned substrate 412 adjacent to the pillars 414 (e.g., within the wells 416) to form the hydrophilic surface 404.
  • the hydrophilic coating can be deposited on the patterned substrate 412 adjacent to the pillars 414 (e.g., within the wells 416) to form the hydrophilic surface 404.
  • a hydrophobic coating can be omitted and the bare surface of the substrate can form the hydrophilic surface 404.
  • the hydrophobic coating can be deposited on the patterned substrate 412 on the upper surface of the pillars 414 to form the hydrophobic surface 402. So configured, the wells 416 with the hydrophilic surface 404 can define the lateral boundary of respective reactor vessels 410.
  • a patterned substrate 500 can be formed by a pattern of hydrophobic surfaces 402 and hydrophilic surfaces 404 alone, without pillars 414 or wells 416.
  • the hydrophobic surfaces 402 and the hydrophilic surfaces can be provided as discussed above and they can define the lateral extent of the one or more reactor vessels 420.
  • a chip 600 that includes a substrate 601 and reactor vessel pillars 602 is inverted during processing of a biological sample.
  • a droplet 603 of a capture liquid suspends from the hydrophilic surface of the reactor vessel pillar 602.
  • the capture liquid droplet 603 contains a biological sample 604 that can be subjected to processing.
  • the RapiGest-based one-pot protocol (Waters, Milford, USA) was adapted for proteomic sample preparation with minimal modification (FIGS. 7-8). Briefly, after cells or other tissue samples were deposited into each chamber of the array, microscopic imaging was used for sample size quantification (cell number, tissue dimensions, etc.). A cocktail containing RapiGest and dithiothreitol was added and incubated at 70°C to lyse cells, extract and denature proteins, as well as reduce disulfide bonds in a single step. The proteins were alkylated and digested using a two-step enzymatic hydrolysis. Finally, the solution was acidified to cleave and inactivate the RapiGest surfactant.
  • Manipulations were conducted in a humidified chamber, and the cover plate was sealed to the nanowell chip during extended incubation steps to minimize evaporation of the nanoliter droplets.
  • the prepared sample was collected into a fused-silica capillary, followed by a two-step wash of the nanowell to maximize recovery (FIG. 7).
  • the collector capillary can be fully sealed and stored in a freezer for months without observable sample loss.
  • the capillary also simplified downstream solid-phase extraction-based cleanup and LC-MS analysis by enabling direct coupling with standard fittings.
  • the average peptide coverage based on MS/MS identification ranged from 7,364 to 17,836, and protein coverage ranged from 1,517 to 3,056 for triplicate groups comprising 10-14, 37-45 and 137-141 cells, respectively (FIG. 14A and 14B).
  • MRR Match Between Runs
  • Maxquant Maxquant
  • FIG. 24A- 24C The ability to identify an average of 3,092 proteins in as small as -10 cells (FIG. 24A- 24C) represents a >500-fold decrease in sample size to achieve similar proteome coverage relative to previously reported methods (Sun, X et al, Chen, W et al., Wannders, L. et al, Huang, E. et al, and Wang, N. et al) (Table 1, below).
  • the proteins were matched identified from 10-14 cells to the reported databases containing protein copy numbers per HeLa cell (Wisniewski, J. et al 2014, and Volpe, P. et al).
  • the absolute copy numbers of 40 proteins in HeLa cell were precisely quantified using spiked-in protein epitope signature tags (PrEST) in combination with SILAC -based isotopic labeling (Volpe, P. et al). Thirty-four of the 40 proteins were identified, and the 6 missed proteins were low in abundance.
  • the corresponding protein copy number per cell ranged from about 5xl0 4 to about 2xl0 7 (Table 2), with 3 expressed at ⁇ l0 5 copies/cell.
  • the detection limit of nanoPOTS for protein is ⁇ 5xl0 5 copies, or ⁇ 830 zmol.
  • AFG3-like protein 2 AFG3L2 369,737
  • Flap endonuclease 1 FEN1 2,019,699
  • Enoyl-CoA hydratase mitochondrial ECHS1 2,105,336
  • Deionized water (18.2 MW) was purified using a Barnstead Nanopure Infinity system (Los Angeles, USA).
  • Dithiothreitol (DTT) and iodoacetamide (IAA) were purchased from Thermo Scientific (St. Louis, USA) and freshly prepared in 50 mM ammonium bicarbonate buffer each day before use.
  • RapiGest SF surfactant (Waters, Milford, USA) was dissolved in 50 mM ammonium bicarbonate buffer with a concentration 0.2% (m/m), aliquoted, and stored at -20 °C until use. Trypsin (MS grade) and Lys-C (MS grade) were products of Promega (Madison, USA).
  • Other unmentioned reagents were obtained from Sigma- Aldrich (St. Louis, USA).
  • the photomask was designed with AutoCAD and printed with a direct-write lithography system (SF-100, Intelligent Micro Patterning LLC, St. Russia, USA).
  • An array of 3 x 7 spots with diameters of 1 mm and a spacing of 4.5 mm was designed on a 25 mm x 75 mm glass slide (soda lime) that was pre-coated with chromium and photoresist (Telic Company, Valencia, USA).
  • chromium and photoresist Telic Company, Valencia, USA.
  • FIG. 3A photoresist exposure
  • development, and chromium etching Transene, Danvers, USA; FIG. 3B
  • the glass slide was hard baked at 110 °C for 10 min.
  • the back side of the slide was protected with packing tape and the glass substrate surface was etched around the patterned photoresist/Cr features using wet etching solution containing 1 M HF, 0.5 M NH 4 F, and 0.75 M HNO 3 at 40 °C for 10 min to reach a depth of 10 pm (FIG. 3C).
  • the remaining photoresist was removed using AZ 400T stripper.
  • the glass slide was thoroughly rinsed with water, dried using compressed nitrogen, and further dried in an oven at 120 °C for 2 h.
  • the chip surface was then cleaned and activated with oxygen plasma treatment for 3 minutes using a March Plasma Systems PX250 (Concord, USA).
  • the glass surface that was not protected with Cr was rendered hydrophobic with a fluorosilane solution containing 2% (v/v) heptadecafluoro-l,l,2,2- tetrahydrodecyl)dimethylchlorosilane (PFDS) in 2,2,4-trimethylpentane (FIG. 3D) for 30 min.
  • the residual silane solution was removed by immersing the chip in 2,2,4-trimethylpentane followed by ethanol. Remaining chromium was removed using chromium etchant (Transene), leaving elevated hydrophilic nanowells on a hydrophobic background (FIG. 3E).
  • the glass spacer was fabricated by milling a standard microscope slide (25 mm x 75 mm x 1 mm) with a CNC machine (Minitech Machinery Corporation, Norcross, USA). Epoxy was used to glue the patterned chip and the glass spacer together.
  • the glass cover was fabricated by spin coating a thin layer of polydimethylsiloxane (PDMS) membrane (l0-pm thickness) onto a standard glass microscope slide of the same dimensions. Briefly, Dow Coming Sylgard 184 silicone base was mixed with its curing reagent at a ratio of 10:1 (w/w) and degassed for 20 min.
  • PDMS polydimethylsiloxane
  • Nanoliter-scale liquid handling system The mixture was coated on the slide by spinning at 500 rpm for 30 s followed by 3000 rpm for 5 min (WS-650, Laurell Technologies, North Wales, USA). Finally, the PDMS membrane was cured at 70 °C for 10 hours. A piece of Parafilm (Bemis Company, Oshkosh, USA) was precisely cut to serve as moisture barrier between the glass spacer and the glass cover.
  • Nanoliter-scale liquid handling system :
  • the capillary probe was fabricated by heating pulling a fused silica capillary (200 pm i.d., 360 pm o.d., Polymicro Technologies, Phoenix, USA) to generate a tapered tip (30 pm i.d., 50 pm o.d.).
  • a home-built program with LabView (Version 2015, National Instruments, Austin, USA) was used to synchronously control the movement of the 3D stages and the liquid dispensing of the syringe pump. To minimize evaporation during the liquid handling procedure, the whole system was enclosed in a Lexan chamber maintained at 95% relative humidity.
  • the syringe pump was set at a withdraw rate of 9 pL/min and an infusion rate of 3 pL/min.
  • the translation stages were operated at a start speed of 1 cm/s, a maximum speed of 30 cm/s, and an acceleration time of 0.5 s. In the typical setup, it took total ⁇ 2 min to dispense one reagent to all the 21 droplets in single chip including the time for withdrawing reagent into the capillary probe, moving of the robotic stages, and dispensing 50 nL reagent into each droplet.
  • the nanowells can be scaled up with the present photolithography-based microfabrication technique.
  • nano wells Up to 350 nano wells can be fabricated on a 25 mm x 75 mm microscope slide and further scale-up is possible with larger substrates.
  • the robot can be simply configured to fit different formats of nanowell array. Because of the high liquid handling speed, 350 droplets could be addressed in ⁇ 30 min.
  • HeLa was grown in Eagle's Minimum Essential Medium (EMEM) supplemented with 10% fetal bovine serum (FBS) and lx penicillin streptomycin.
  • EMEM Eagle's Minimum Essential Medium
  • FBS fetal bovine serum
  • HeLa cells were collected in a 10 mL tube and centrifuged at 1200 rpm for 10 minutes to remove culture media. The cell pellet was further washed three times with 10 mL of lx PBS buffer. The cells were then suspended in 1 mL PBS buffer and counted to obtain cell concentration.
  • Eppendorf protein low-binding vials (0.5 mL) were used throughout the process. Cells were lysed at a concentration of 5x in 0.1% RapiGest and 5 mM DTT in 50 mM ammonium
  • the chip was washed with isopropanol and water to minimize contamination ⁇
  • the liquid handling system was configured to minimize cross contamination by adjusting the vertical distance between the probe tip and the nanowell surface, which was previously termed semi-contact dispensing (Zhu, Y. et al 2014).
  • RapiGest (Yu et al. 2003) (0.2%) solution with 10 mM DTT in 50 mM ammonium bicarbonate (ABC) was added into the nanodroplets that had been preloaded with cells.
  • Ammonium bicarbonate (ABC)
  • the second step 50 nL of IAA solution (30 mM in 50 mM ABC) was dispensed to alkylate sulfhydryl groups by incubating the chip in the dark for 30 minutes at room temperature.
  • 50 nL enzyme solution containing 0.25 ng Lys-C in 50 mM ABC was added and incubated at 37 °C for 4 h for predigestion.
  • 50 nL of enzyme solution containing 0.25 ng trypsin in 50 mM ABC was added into each droplet and incubated overnight at 37 °C for tryptic digestion.
  • formic acid solution (30%, v/v) was dispensed and allowed to incubate for 1 h at room temperature to cleave RapiGest surfactant for downstream analysis.
  • the chip was completely sealed during cell counting, incubation, and transfer procedures. During each dispensing step, the chip was opened and closed within the humidity chamber to minimize droplet evaporation.
  • the total dispensed volume in each droplet was 300 nL, and the final volume was typically ⁇ 200 nL, some evaporative losses clearly occurred.
  • the nanowell was twice washed with 200-nL buffer A and the wash solutions were also collected in the same capillary.
  • a section of capillary containing a train of plugs consisting of carrier, air bubble, sample, and wash solutions was then cut from the syringe pump.
  • the capillary section was sealed with Parafilm at both ends and stored at -20 °C for short-term storage or -70 °C for long-term storage.
  • the SPE precolumn and LC column were slurry-packed with 3 -pm C18 packing material (300- A pore size, Phenomenex, Terrence, USA) as described previously (Shen, Y. et al 2004, and Shen, Y. et al. 2003).
  • the SPE column was prepared from a 4-cm-long fused silica capillary (100 pm i.d., 360 pm o.d., Polymicro Technologies, Phoenix, AZ).
  • the LC column was prepared from a 70-cm Self-Pack PicoFrit column with an i.d. of 30 pm and a tip size of 10 pm (New Objective, Wobum, USA).
  • the sample storage capillary was connected to the SPE column with a PEEK union (Valeo instruments, Houston, USA).
  • Sample was loaded and desalted in the SPE precolumn by infusing buffer A (0.1% formic acid in water) at a flow rate of 500 nL/min for 20 minutes with an nanoACQUITY UPLC pump (Waters, Milford, USA).
  • the SPE precolumn was reconnected to the LC column with a low-dead-volume PEEK union (Valeo, Houston, USA).
  • the LC separation flow rate was 60 nL/min, which was split from 400 nL/min with a nanoACQUITY UPLC pump (Waters, Milford, USA).
  • Precursor ions with charges of +2 to +7 were isolated with an m/z window of 2 and fragmented by high energy dissociation (HCD) with a collision energy of 28%.
  • the signal intensity threshold was set at 6000.
  • dynamic exclusion with duration of 90 s and mass tolerance of ⁇ 10 ppm was utilized.
  • MS/MS scans were performed in the Obitrap.
  • the AGC target was fixed at 1E5. For different sample inputs, different scan resolutions and injection times were used to maximize sensitivity (240k and 502 ms for blank control and ⁇ l0-cell samples; l20k and 246 ms for ⁇ 40-cell samples; 60k and 118 ms for ⁇ l 40-cell samples).
  • the match tolerance, de novo tolerance, and deisotoping tolerance for MS/MS search were 20, 10, and 7 ppm, respectively.
  • the minimum peptide length was 7 amino acids and maximum peptide mass was 4600 Da.
  • the allowed missed cleavages for each peptide was 2.
  • the second peptide search was activated to identify co-eluting and co fragmented peptides from one MS/MS spectrum. Both peptides and proteins were filtered with a maximum false discovery rate (FDR) of 0.01.
  • FDR maximum false discovery rate
  • the Match Between Runs feature with a match window of 0.7 min and alignment window of 20 min, was activated to increase peptide/protein identification of low-cell-number samples. LFQ calculations were performed separately in each parameter group that containing similar cell loading.
  • Perseus (Tyanova, S. et al. 2016) was used to perform data analysis and extraction. To identify the significantly changed proteins from a non-diabetic donor and a T1D donor, the datasets were filtered to contain 3 valid LFQ intensity values in at least one group. The missing values were imputed from normal distribution with a width of 0.3 and a down shift of 1.8. Two sample T-test with a minimal fold change of 2 and a FDR of 0.01 was performed for statistical analysis. The extracted data were further processed and visualized with OriginLab 2017. Global scaling normalization was achieved using scaling coefficients calculated as the ratio of peptide abundance to the median peptide abundance measured for each loading set.
  • the nanoPOTS platform provided a robust, semi-automated nanodroplet-based proteomic processing system for handling extremely small biological samples down to as few as 10 cells with high processing efficiency and minimal sample loss. This capability opens up many potential biomedical applications from small cell populations and clinical specimens such as tissue sections for characterizing tissue or cellular heterogeneity. Reproducible quantitative proteome
  • the platform effectively addressed the bottleneck of sample losses during proteomics sample preparation by performing all of the multi-step reactions within a single nanodroplet of ⁇ 200 nL volume, while all previous methods still suffer from a significant degree of protein/peptide losses during processing.
  • the nanodroplet processing mechanism allowed us to perform each reaction at optimal concentrations. For example, by preserving the 20-50:1 ratio
  • the nanoPOTS has an open structure, which is inherently suitable for integration with upstream and downstream proteomic workflows, including sample isolation for processing and transfer for LC-MS analysis.
  • Islet Area (mhi 2 ) Islet volume (mhi 3 ) Cell Islet equivalents
  • nanoPOTS represented a highly promising platform towards single mammalian cell proteomics with optimized processing volumes and further refinements to the LC-MS platform.
  • the total processing volume could be reduced to the low- nanoliter range to further minimize sample loss.
  • FACS or other cell isolation techniques should be used to isolate single cells into nano wells without the minimal exogenous contamination from, e.g., secreted proteins or lysed cells.
  • NanoLC columns with narrower bore Shen, Y. et al. 2004, and Shen, Y. 2003
  • ESI emitter technology accommodating the lower resulting flow rates (Smit,
  • nanoPOTS should also provide a viable path towards tissue imaging at the proteome level by performing in-depth spatially resolved proteome measurements for specific cellular regions.
  • Example 3 nanoPOTS with LCM and capture liquid
  • Nanowells are prepopulated with DMSO droplets to serve as a sacrificial capture medium for small tissue samples in the nanoPOTS chip (FIGS. 29A-29E) as described below in detail.
  • Nanowell chip fabrication The nanowell chip consisted of three parts including a nanowell-containing substrate, a spacer, and a cover plate.
  • the nanowell substrate was fabricated with the similar procedures described previously. (Liu, Anal. Chem. 2017, 89(1), 822-829; Zhu, Anal. Chem. 2010, 82 (19), 8361-8366) Briefly, a glass slide (25 mm x 75 mm) with pre-coated chromium and photoresist (Telic company, Valencia, CA) was used as starting material.
  • Standard photolithography and wet etching procedures were employed to generate an array of pedestals with a diameter of 1.2 mm, a height of 10 pm, and a spacing of 4.5 mm between adjacent pedestals on the slide.
  • the exposed surfaces surrounding the pedestals were treated to be hydrophobic with 2% (v/v) heptadecafluoro-l,l,2,2-tetrahydrodecyl)dimethylchlorosilane (PFDS) (Sigma Aldrich) in 2,2,4-trimethylpentane.
  • PFDS heptadecafluoro-l,l,2,2-tetrahydrodecyl)dimethylchlorosilane
  • the glass spacer was laser-machined (Coherent Inc., Santa Clara, CA) on a standard 1.2-mm-thick microscope slide. The machining process removed the center region of the slide, leaving a thin frame of ⁇ 5 mm in width.
  • the machined slide was glued to the nanowell substrate using a silicone adhesive, and served as a spacer to limit the headspace of the nanowells after reversibly sealing to a cover plate to minimize evaporation during incubation steps, while prevent contact of the droplet reactors with the cover plate.
  • the cover plate was produced by spin coating of a thin layer of Sylgard 184 and its curing reagent (10/1, v/v) (Dow Coming) at a spin speed of 500 rpm for 30 s followed by 3000 rpm for 5 min.
  • the cover plate was baked at 70 °C for 10 hours to generate a ⁇ 30-pm-thick polydimethylsiloxane (PDMS) layer.
  • PDMS polydimethylsiloxane
  • Tissue preparation Rats were anesthetized by intra-peritoneal injection of chloral hydrate. Rat brain was dissected and snap frozen in liquid nitrogen. The brains were stored at -80 °C until use. A cryostat (NX-70, Thermo Scientific, St. Louis, MO) was used to cut tissues to a thickness of 12 pm. The chuck and blade temperatures were set as -16 °C and -20 °C, respectively. The tissue sections were deposited on PEN membrane slides (Carl Zeiss Microscopy, Germany) and stored at -80 °C.
  • the tissue section was removed from the freezer or dry ice box and immediately immersed into 70% ethanol to fix proteins. The tissue was then rehydrated in deionized water for 30 s and stained in Mayer’s hematoxylin solution for 1 min. Excess dye was rinsed with water and the tissue was blued in Scott’s Tap Water Substitute for 15 s. Next, 70% ethanol was used to dehydrate the tissue and a 50% dilution of eosin Y solution (v/v in ethanol) was applied for 1-2 s by a quick dip.
  • eosin Y solution v/v in ethanol
  • the tissue sample was further dehydrated by immersion twice in 95% ethanol for 30 s, twice in 100% ethanol for 30 s, and finally in xylene for 2 min. All the procedures were performed in a fume hood and the slide was blotted on absorbent paper between different solutions to minimize carry over. The processed tissue could be directly used for LCM or stored at -80 °C until use.
  • NanoPOTS proteomic sample processing Before processing, DMSO droplets were evaporated to dryness by keeping the nanowell chip in a vacuum desiccator for 10 to 15 min (FIG. 29E). Reagent dispensing was performed using the robotic system as described previously. (Zhu, Anal. Chem. 2013, 85 (14), 6723-6731; Zhu, Sci. Rep. 2015, 5, 9551; Zhu, Sci. Rep. 2014, 4, 5046) Briefly, 100 nL lx PBS buffer containing 0.2% DDM surfactant and 5 mM DTT was added into each nanowell. The chip was incubated at 70 °C for 1 h for protein extraction and denaturation.
  • Proteins were then alkylated by adding 50 nL of 30 mM IAA in 50 mM ammonium bicarbonate (ABC) in each reaction and then incubating for 40 min in the dark. A two-step digestion was performed at 37 °C with Lys-C and trypsin for 4 h and 8 h, respectively. Finally, the digested peptide samples were collected and stored in a fused silica capillary (4 cm long, 200 pm i.d., 360 pm o.d.). Each nanowell was washed twice with 200 nL, 0.1% formic acid aqueous buffer and the wash solution was also collected into the same capillary to maximize sample recovery.
  • a two-step digestion was performed at 37 °C with Lys-C and trypsin for 4 h and 8 h, respectively.
  • the digested peptide samples were collected and stored in a fused silica capillary (4 cm long, 200 pm i.d., 360 pm o.d.). Each nanowell
  • the distance between the capillary distal end and the nanowell surface was kept at 100 pm during the sample aspiration process.
  • the capillary was sealed with Parafilm at both ends and stored at -70 °C until analyzed.
  • NanoLC-MS/MS for protein identification.
  • Samples in the collection capillary were desalted and concentrated on a solid phase extraction (SPE) column (75-pm-i.d. fused silica capillary packed with 3 pm, 300 A pore size C18 particles, Phenomenex, Terrence, CA).
  • Peptides were separated using a 60-cm-long, 30-pm-i.d. nanoLC column (3 pm, 300 A pore size C18 particles, Phenomenex) with an integrated electrospray emitter (Self-Pack PicoFrit column, New Objective, Wobum, MA).
  • a nanoUPLC pump (Dionex UltiMate NCP-3200RS, Thermo Scientific, Waltham, MI) was used to deliver mobile phase to the LC column.
  • a tee interface was used to split the LC flow rate from 300 nL/min to 50 nl/min for the 30-pm-i.d. LC column.
  • a linear lOO-min gradient starting from 8% buffer B (0.1% formic acid in acetonitrile; buffer A: 0.1% formic acid in water) to 22%, followed by a 1 -min linear increase to 35% buffer B.
  • the column was washed with 90% buffer B for 5 min and re equilibrated with 2% buffer B for 20 min prior to the subsequent analysis.
  • Peptides were ionized at the nanospray source using a potential of 2 kV.
  • An Obitrap Fusion Lumos Tribrid MS (ThermoFisher) operated in data dependent mode to automatically switch between full scan MS and MS/MS acquisition with a cycle time of 2 s.
  • the ion transfer capillary was heated to 250 °C to accelerate desolvation, and the S lens was set at 30.
  • Full-scan MS spectra (m/z 375-1600) were acquired in the Orbitrap analyzer with 120,000 resolution ( m/z 200), and AGC target of 3 x 10 6 , and a maximum ion accumulation time of 246 ms.
  • Precursor ions with charges from +2 to +7 were isolated with an m/z window of 2 and were sequentially fragmented by high energy dissociation (HCD) with a collision energy of 30%.
  • the AGC target was set at 1 x 10 5 .
  • MS/MS scan spectra were acquired in the Orbitrap with an ion accumulation time of 502 ms and resolution of 240,000 for 50-pm-diameter tissue sample, an ion accumulation time of 246 ms and 120,000 resolution for l00-pm-diameter tissue sample, or an ion accumulation time of 118 ms and 60,000 resolution for 200-pm-diameter tissue samples, respectively.
  • FDR false discovery rate
  • tissue pieces with a diameter of 20 pm correspond to single cells in most of mammalian tissues, demonstrating the potential of the present approach for single-cell isolation and analysis.
  • proteome coverage significantly increased for small tissue samples.
  • a possible explanation for this result is that protein extraction efficiency was improved after hydrophobic lipids were removed by DMSO in the brain tissue.
  • Protein extraction from tissue samples was found to be more challenging than for cultured cells, especially for tissue containing high lipid content such as brain.
  • Various approaches have been developed to address this challenge by employing strong detergents or organic solvent in the extraction buffer.
  • DMSO is expected to have high solubility for most lipids, and thus could dissolve them prior to protein extraction.
  • sample losses in detergent removing steps including buffer exchange and spin columns was avoided using the inventive approach described herein.
  • FIGS. 31D and 31E show the linear increase of unique peptide and protein identifications with tissue size. As expected, nearly all peptides and proteins identified in the smaller tissues were also identified in larger tissues (FIG. 31D), demonstrating analytical sensitivity dominated the proteome coverage.
  • the LCM-DMSO-nanoPOTS system provided >25 times better spatial resolution with higher proteome coverage.
  • GABA receptors GABA receptors
  • GABA receptors GABA receptors
  • GABA receptors GABA receptors
  • GBRB1, GABRB2, GABRB2, and GABRG2 GABA receptors
  • GABA receptors GABA receptors
  • GRM2, GRM3, GRM5 GPR158, GRIK3, GRIN1, GRIN2a, and GRIN2b.
  • the spatial distances were from 116 pm to 716 pm between the same regions, and from 424 pm to 1,727 pm between different regions (FIG. 32A), showing the high spatial resolution of the present measurement.
  • FIG. 32B For each region, six samples were processed and four of them were submitted for LC-MS analysis (FIG. 32B).
  • MLR Match Between Runs
  • AMT LC retention times
  • CTX and CP shows lower in correlation coefficients from 0.94 to 0.97, while CC has lowest correlations (from 0.83 to 0.91) with the other two regions. Such differences are also indicated in the morphology of the brain tissue (FIG. 32A).
  • the LCM-DMSO-nanoPOTS system was tested to see if it could be applied to distinguish different tissue types.
  • Unsupervised principal component analysis (PCA) was used to process the LFQ intensity data from the 12 tissue samples. As shown in FIG. 33A, the three tissue regions were segregated based on component 1 and component 2, which accounted for 65.5% and 15.6%, respectively. All four biological replicates were well clustered within the corresponding tissue region without overlap with other regions, suggesting the present system can efficiently distinguish tissue types based on their protein expressions.
  • HCA hierarchical clustering analysis
  • the results described herein demonstrate that the LCM- capture liquid-nanoPOTS platform significantly advances spatially-resolved proteomics by improving the resolution and increasing the sensitivity.
  • the use of DMSO droplets not only served to efficiently capture dissected tissue pieces as small as 20-pm diameter (single-cell scale) into nanowells, but also significantly improved the proteome coverage.
  • the whole workflow can be fully automated without manual transfer, and thus sample loss and protein contamination is minimized.
  • This platform may play an important role in proteomic analyses and may be applied to various fields including biomedical research, clinical diagnosis, microbial community, and plant science.
  • the LCM- capture liquid-nanoPOTS platform should be readily extended to other omics studies requiring tissue isolation and nanoscale processing, such as transcriptomics, lipidomics, and metabolomics.
  • aspects of the sample preparation, processing, and/or transfer are configured to facilitate automation and/or performance by robotic sub-systems.
  • systems and methods for proteome analysis enable high-throughput processing and/or protein imaging that utilizes label-free nanoproteomics to analyze tissue voxels. Quantitative images for thousands of proteins with very fine spatial resolution can be generated. At least twenty-five-fold increases can be obtained in protein coverage compared to other technologies.
  • MSI mass spectrometry imaging
  • a probe e.g., laser, ion beam, liquid junction
  • mass spectrometry imaging serially moves across a surface to desorb or extract biomolecules that are then directly analyzed by mass spectrometry.
  • This allows for the creation of detailed spatial maps that reveal the native distribution of biomolecules at the surface without labels or pre-treatments.
  • molecules are transmitted directly from the tissue to the mass spectrometer without separation, limiting the dynamic range of observed analyte concentrations and restricting detection to the most abundant species.
  • ionization process for a given analyte is impacted by other constituents in the mixture (so-called“matrix”), and since ionization efficiency is strongly influenced by the sample matrix, quantitative comparisons are often challenging. These factors are compounded when imaging proteins, many of which are present in significantly lower abundances than many metabolites and lipids. Additionally, MS detection of intact protein species is challenging due to poor ionization efficiency, and larger isotopomer envelopes, further reducing the achievable signal-to-noise ratio. As a result, MSI techniques are not sufficiently capable of imaging at the proteome level.
  • a biological sample 3503 is placed in one of a plurality of nanoPOTS reactor vessels 3502 on a nanoPOTS plate.
  • the biological sample can be a tissue sample 3505 obtained by an LCM laser 3504, as illustrated.
  • a complement of proteins in the biological sample can be digested 3506 to yield a processed sample comprising peptides 3507 related to the complement of proteins.
  • a complement of proteins in the biological sample can be extracted and/or purified to yield a processed sample.
  • the processed sample 3507 is extracted from the nanoPOTS reactor vessel with a syringe 3510, leaving minimal amounts of the processed sample 3509 in the substantially empty NanoPOTS reactor vessel 3508.
  • the extracted processed sample is dispensed into a well 3511 on a well plate 3512 having a plurality of wells.
  • the well can be pre-loaded with a volume of liquid carrier buffer to receive the extracted processed sample.
  • a syringe 3513 dispenses a volume of a wash solution into the NanoPOTS reactor vessel 3508. Residual amounts of the processed sample are incorporated into the wash solution.
  • the contents of the NanoPOTS reactor vessel 3514 are transferred in a syringe 3515 to the well 3511, thereby diluting the contents of the well and yielding a diluted sample.
  • the washing of the nanoPOTS reactor vessel and transferal of the vessel contents can be repeated to ensure that the maximum amount of processed sample is transferred into the well.
  • the diluted sample is then transferred 3516 from the well to a MS-based analytical instrument 3517.
  • the transfer may be accomplished using a syringe tip 3519 having a notch 3518 in the proximal end at the face surface.
  • the syringe is inserted into the well such that the tip contacts, or nearly contacts, the well plate.
  • the notch enables maximum extraction from the well by preventing a seal between the syringe tip and the well surface.
  • the notch 3518 is located at the end 3606 of a syringe tip 3519 and is not located on the side 3605 of the syringe tip.
  • the notch is aligned with at least a portion of the aperture 3604 at the end to allow fluid flow via the notch into the channel 3603 in the syringe.
  • the syringe tip is inserted in a well and the tip contacts the well surface 3601. In certain embodiments, the tip can nearly contact the well surface without actual contact.
  • the notch 3518 prevents a seal from preventing extraction of the liquid contents 3602 of the well.
  • the notch is created by using a copper electrode from an electrical discharge machining tool (EDM) to remove a portion of the syringe tip from the end of the tip.
  • EDM electrical discharge machining tool
  • the syringe can have a plurality of notches in the end of the syringe tip.
  • a tissue sample 3708 can be taken from a section of tissue 3701. The tissue sample can be voxelated and each voxel 3702 can be co-registered with a
  • NanoPOTS reactor vessel 3704 and a well plate well 3705 can be achieved by overlaying a grid on the tissue sample and using a LCM laser to dissect voxels according to the grid.
  • a protein image map can be generated correlating the presence, and in some embodiments the quantity, of each of a plurality of proteins with the voxel (i.e., spatial region of the tissue sample) from which the protein originated (see image maps in element 3709).
  • the tissue sample voxel has dimensions less than or equal to 500 mhi. In other embodiments, the tissue sample voxel has dimensions less than or equal to 100 mhi.
  • the generation of a visual representation of the protein identifications mapped to a spatial region of a tissue sample utilizes software executed by processing circuitry to search, process and visualize the data.
  • each peptide can be identified by comparing the experimental tandem mass spectra to theoretical tandem mass spectra of a collection of peptides in a protein.
  • Relative protein quantifications can be calculated based on the MS peak intensities for the collection of peptides associated with the identified protein.
  • the identified and quantified proteins can then be assigned to the spatial region with which the originating well and nanoPOTS reactor vessel wsa co-registered.
  • transgenic mice with uterine specific inactivation of WntSa ⁇ ( Wnt5a loxm ° xP ) were generated.
  • This transgenic mouse model of impaired embryo implantation contains morphological, cellular, and molecular changes in the uterus including disrupted luminal epithelial evaginations (crypts) at the antimesometrial domain. These crypts are an essential step in the receptive uterus prior to embryo attachment ⁇ Uterine tissue from one WntSa ⁇ mouse was sectioned with a thickness of 12 pm using a cryostat.
  • the temperatures of chuck and blade were set at -16 °C and -20 °C for liver tissues and -16 °C and -20 °C for uterus tissues.
  • the tissue sections were deposited on PEN membrane slides and stored in a freezer at -80 °C.
  • Tissue fixative solution (70% ethanol) were pre-cooled in 4 °C before use. Tissue sections were immediately immersed into 70% ethanol for 15 s after removal from the -80 °C freezer or dry-ice box. Rehydration was performed for 30 s in deionized water. Next, the tissue sections were immersed in Mayer’s hematoxylin solution (Sigma- Aldrich, St. Louis, USA) for 1 min, dipped twice in deionized water to remove excess dye solution, and immersed in Scott’s Tap Water Substitute (Sigma- Aldrich ) for 15 s to dye the tissues.
  • tissue dehydration was performed by sequentially immersing the tissue sections in 70% ethanol for 1 min, 95% ethanol for 1 min, 100% ethanol for 1 min, and xylene for 2 min.
  • the sections were dried in a fume hood for 10 min, which can be directly used or stored in -80 °C until use.
  • NanoPOTS plates comprising nanowell chips were fabricated from glass slides with precoated chromium and photoresist layers (Telic company, Valencia, USA) using standard photolithography and wet chemical etching procedures.
  • An array of 3 x 9 nanowells i.e., NanoPOTS reactor vessels
  • DWL Direct-Write Lithography
  • the slides were etched in a solution of 2:4:4 (v:v:v) buffered hydrofluoric acid, hydrochloric acid, and water at an etch rate of 1 pm/min for 10 min. After drying in 120 °C for 2 h, the slides were treated with 2% (v/v) heptadecafluoro-l,l,2,2-tetrahydrodecyldimethylchlorosilane in 2,2,4-trimethylpentane. After removing the remaining chromium layer, an array of hydrophilic spots was formed on a hydrophobic background.
  • a glass frame (machined by Coherent Inc., Santa Clara, CA) with a thickness of 1 mm and a width of 5 mm was affixed to the nanowell slide using silicone adhesive.
  • a sealing cover plate was fabricated by spin-coating a layer of polydimethylsiloxane (PDMS, 30-pm in thickness). The sealing cover slide was used to reversibly seal the nanowell chip during reaction incubation.
  • PDMS polydimethylsiloxane
  • the “CenterRoboLPC” function with an energy level of delta 10 and a focus level of delta 5 was used to catapult tissue voxels into DMSO droplets.
  • The“CapCheck” function was activated to confirm successful sample collection from tissue sections to DMSO droplets.
  • the nano well chip was heated to 70 °C for 10 min to evaporate the DMSO droplet.
  • a nanoliter-resolution robotic liquid handling platform was employed to dispense reagents into nanowells.
  • a cell lysis buffer containing 0.2% (w/v) n -dodec y 1 - b - D - m a 1 tos i de (DDM, Sigma- Aldrich), 5 mM Dithiothreitol (DTT) and lx PBS was applied into each nano well with a volume of 100 nL.
  • the chip was incubated at 70 °C for 1 h for cell lysis, protein extraction and denaturation.
  • the processed samples were transferred into 96-well PCR well plates for LC-MS analysis.
  • the 96-well plate was prefilled with 25 pL of 0.1% TFA and 0.02% DDM aqueous buffer.
  • the robotic platform was used to aspirate nanoliter samples from the nanowells and dispense the samples into the 25 -pL buffer.
  • Each nanowell was washed twice with 200 nL of a wash solution that comprised the same buffer to maximize sample recovery.
  • the 96-well plates were sealed with sealing tape (Nunc, Thermo Scientific) and stored at -20 °C.
  • a LC cart was employed to automatically perform sample injection, sample cleanup, and LC separation.
  • the cart consisted of a PAL autosampler (CTC ANALYTICS AG, Zwingen, Switzerland), two Cheminert six-port injection valves (Valeo Instruments, Houston, USA), a binary nanoUPLC pump (Dionex UltiMate NCP-3200RS, Thermo Scientific), and a HPLC sample loading pump (1200 Series, Agilent, Santa Clara, USA).
  • a QExactive Plus Orbitrap MS (Thermo Scientific) was used to analyze the separated peptides.
  • a 2.2 kV high voltage was applied at the ionization source to generate electrospray and ionize peptides.
  • the ion transfer capillary was heated to 250 °C to desolvate droplets.
  • the S-lens RF level was set at 70.
  • Data dependent mode was employed to automatically trigger precursor scan and MS/MS scans. Precursors were scanned at a resolution of 35,000, an AGC target of 3E6, a maximum ion trap time of 50 ms, and mass range of 375-1800.
  • Top- 12 precursors were isolated with an isolation window of 2, an AGC target of 1E5, a maximum ion trap time of 150 ms, and then fragmented by high energy collision (HCD) with an energy level of 32%. A dynamic exclusion of 30 s was used to minimize repeated sequencing. MS/MS spectra were scanned at a resolution of 17,500. [000215] Data Analysis.
  • the dominant cell population study contained 15 LC-MS/MS instrument runs associated with 15 unique biological samples, 5 stromal (S) samples, 5 luminal epithelium (LE) samples, 5 glandular epithelium (GE) samples, where 100-200 ng of these unique cell populations were captured from 3-5 sections for each of the 15 unique biological samples. From the Maxquant match-between-run search 19,952 peptides had at least 2 observations across the 15 analyses. The algorithm RMD-PAV was used to identify any outlier biological samples. Samples were also examined via Pearson correlation. No samples were identified as outliers.
  • Protein quantification was performed using r-rollup, which scales the peptides associated with each protein by a reference peptide and then sets their median as the protein abundance.
  • the reference peptide is the peptide with the least missing data.
  • Pairwise univariate statistical comparisons were carried out between each of the three cell types using a Tukey-adjusted ANOVA or a Holm-corrected g-test to compare each pair of dominant cell types for each of the 2,940 proteins.
  • the three statistical comparisons of interest were (1) LE vs GE, (2) S vs GE, and (3) S vs LE.
  • the nanoPOTS imaging MS study was used to create 2D protein images of tissue sections comprised of our three cell types of interest. Imaged areas were taken from the center of uterine sections, enabling visualization of the uterine proteomic landscape orchestrating embryo implantation.
  • the S dominant section, Image 1 contained 24 LC-MS/MS instrument runs associated with 24 unique biological samples, 4 containing GE & S, 8 containing LE, and 12 containing S.
  • the LE dominant section, Image 2 contained 24 LC-MS/MS instrument runs associated with 24 unique biological samples, 2 containing GE & S, 14 containing LE, and 8 containing S. MaxQuant analysis of Image 1 characterized 8,065 measured unique peptides corresponding to 1,658 unique proteins that had at least 2 observations across the 24 runs.
  • ranges specifically include the values provided as endpoint values of the range.
  • a range of 1 to 100 specifically includes the end point values of 1 and 100. It will be understood that any sub-ranges or individual values in a range or sub-range that are included in the description herein can be excluded from the claims herein.

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Abstract

L'invention concerne des procédés et des systèmes d'analyse du protéome qui sont au moins en partie automatisés et/ou exécutés de manière robotisée. Selon certains aspects, les procédés et les systèmes décrits dans la présente description peuvent fournir rapidement et efficacement une identification de protéine de chacune des protéines d'un protéome, ou d'un complément de protéines, obtenu à partir de quantités extrêmement faibles d'échantillons biologiques. Les protéines identifiées peuvent être imagées quantitativement sur une région spatiale. L'automatisation et la robotique améliorent les rendements des procédés et des systèmes, ce qui permet une imagerie et/ou une analyse rapides de protéines du protéome.
EP19739420.8A 2018-05-31 2019-05-30 Procédés et systèmes d'analyse et d'imagerie du protéome Pending EP3803413A1 (fr)

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US15/993,949 US11719702B2 (en) 2016-11-07 2018-05-31 Methods and systems of proteome analysis and imaging
PCT/US2019/034677 WO2019232226A1 (fr) 2018-05-31 2019-05-30 Procédés et systèmes d'analyse et d'imagerie du protéome

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US11719703B2 (en) 2018-01-17 2023-08-08 Northeastern University Mass spectrometry technique for single cell proteomics
US20240201200A1 (en) * 2021-04-23 2024-06-20 Northeastern University Miniaturized Proteomic Sample Preparation

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EP3535418B1 (fr) * 2016-11-07 2021-12-15 Battelle Memorial Institute Préparation et analyse d'échantillons biochimiques de taille nanométrique

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