JPWO2006057444A1 - Method for automatic diagnosis of cell differentiation - Google Patents
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Abstract
非破壊的、かつ、非侵襲的に細胞の分化度を自動診断できる細胞の分化度自動診断方法を提供することを課題とし、具体的には、細胞分化による細胞の形態変化を観察手段で観察し、得られた観察データを基に、細胞の形態変化を形態変化度として数値化して、細胞の分化度を診断する。It is an object of the present invention to provide a method for automatically diagnosing the degree of differentiation of cells which is capable of non-destructively and non-invasively diagnosing the degree of differentiation of cells. Then, based on the obtained observation data, the morphological change of the cells is quantified as the morphological change degree to diagnose the differentiation degree of the cells.
Description
本発明は、細胞の分化度自動診断方法に関するものである。さらに詳しくは、本発明は、非破壊的、かつ、非侵襲的に細胞の分化度を自動診断できる、新しい細胞の分化度自動診断方法に関するものである。 The present invention relates to a method for automatically diagnosing cell differentiation. More specifically, the present invention relates to a new method for automatically diagnosing the degree of differentiation of cells which is capable of non-destructively and non-invasively diagnosing the degree of differentiation of cells.
近年、生体細胞や組織を体外で培養し、得られた細胞や組織を体内、もしくは、体表面の欠損部位、不全部位等の修復や治療に利用するという「再生医療」の研究が発展し、その活用が期待されている。
移植等の再生医療を目的とした、生体細胞や組織の体外培養は、細菌やマイコプラズマ、ウイルス、また埃等の混入による汚染を防止できる培養環境で行う必要がある。つまり、厳重に管理された環境と、施設で行わなければならない。たとえば、クラス１００のクリーンルーム内で、作業者が無人衣を着用し、さらにクリーンベンチを用いて高度な無菌操作を行うことで、上記汚染を防止しつつ、再生医療を目的とした細胞等の体外培養を行う方法が知られている。
また、生体細胞や組織を体外で増殖させたり、分化させたりする培養作業を、そのほとんどの工程が無菌的、かつ、自動的に（つまり、作業者の介在がほとんど無い）行える自動培養装置が提案されている（たとえば、特許文献１、特許文献２等）。この自動培養装置によって、無菌操作を自動で実施できるとともに、作業者の介在がほとんどないため、作業者からの汚染を防止することができる。さらに、特殊な施設（特殊なクリーンルーム等）の設置も必要なくなり、再生医療の研究開発におけるコストの削減や、再生医療の研究開発の発展に貢献することができる。
ところで、このような細胞や組織の体外培養の工程の一つに「時間管理」があるが、この時間管理のためには、培養経過の測定が重要である。その中でも、特に培養中の細胞や組織の分化度を測定することが重要である。たとえば、細胞や組織の分化度の変化を経時的に追跡、測定することによって、＜１＞必要な細胞量まで細胞が分化した時点を判断して、培養を中止すること、あるいは、＜２＞細胞の分化が不十分であると判断して、培養の継続すること等を効率よく認識することができる。また、分化度の測定は、培養条件を途中で変更する際の判断材料とすることができ、重要な測定項目である。
そして、特に、再生医療を目的とした細胞の分化度の測定に際しては、極めて高い品質管理が要求されるという観点から、測定器具や装置等が培養中の細胞や組織、またその周囲の培養液等に接触することは極力避けることが重要である。したがって、再生医療を目的とした細胞や組織の培養の自動化には、非接触的、非破壊的、あるいは、非侵襲的に培養中の細胞や組織の分化度を測定、診断することが必要となる。
そこで、従来の細胞の分化度の診断としては、マウス等の実験動物に分化度の診断目的の細胞を移植して、移植後の経過を観察することで、分化度を診断する方法が提案されている（たとえば、特許文献３）。また、細胞や組織の分化状態に依存して細胞表面に発現する特定のタンパク質の量を測定して細胞の分化度を診断する方法や、分化状態に依存して発現する特定の遺伝子の発現度合いを解析することで、細胞の分化度を診断する方法等も提案されている（たとえば、特許文献４、特許文献５等）。
しかしながら、上記の特許文献３記載の方法では、細胞や組織を実験動物に効率よく移植するには一定水準以上の熟練した技術を要し、自動化することは困難であり、また実験成果を得られるのは数週間から数ヶ月という長い時間を要し、その間に細胞や組織が死滅したり変質するという問題があった。
また、特許文献４記載のタンパク質の量を測定する方法では、自動的に行う装置は開発されておらず、また測定した細胞や組織は、患者に移植することは安全面からの観点から行うことはできず、測定の目的のために多数の細胞や組織を破壊する必要があった。さらに、特許文献５記載の遺伝子の発現度合いを解析する方法でも、解析には最低でも２から３日を要し、また解析の目的で多数の細胞を破壊する必要があるという問題があった。
そこで本発明は、以上のとおりの背景から、従来の問題を解消し、非破壊的、かつ、非侵襲的に、しかも短時間で細胞の分化度を自動診断できることを課題としている、新しい細胞の分化度自動診断方法を提供する。
In vitro culture of living cells and tissues for the purpose of regenerative medicine such as transplantation needs to be performed in a culture environment that can prevent contamination due to contamination with bacteria, mycoplasma, viruses, dust, and the like. In other words, it must be done in a tightly controlled environment and facility. For example, in a class 100 clean room, an operator wears unmanned clothing and further performs a high-grade aseptic operation using a clean bench to prevent the above-mentioned contamination and to prevent cells such as cells outside the body for regenerative medicine. Methods for culturing are known.
In addition, there is an automatic culture device that can perform culturing work for proliferating and differentiating living cells and tissues outside the body aseptically and automatically (that is, with almost no operator intervention). Proposed (for example, Patent Document 1 and Patent Document 2). With this automatic culture device, aseptic operation can be automatically performed, and since there is almost no intervention by the operator, it is possible to prevent contamination from the operator. Furthermore, it is not necessary to install a special facility (a special clean room, etc.), which can contribute to the reduction of costs in the research and development of regenerative medicine and the development of the research and development of regenerative medicine.
By the way, there is "time control" as one of the steps of such in vitro culture of cells and tissues, but for this time control, measurement of the culture process is important. Among them, it is particularly important to measure the degree of differentiation of cells or tissues in culture. For example, by observing and measuring changes in the degree of differentiation of cells or tissues over time, <1> determining when the cells have differentiated to the required amount of cells and then terminating the culture, or <2> It is possible to judge that cell differentiation is insufficient and efficiently recognize that the culture is continued. In addition, the measurement of the degree of differentiation can be used as a judgment material when changing the culture conditions on the way, and is an important measurement item.
And, in particular, in measuring the degree of differentiation of cells for the purpose of regenerative medicine, from the viewpoint that extremely high quality control is required, cells and tissues in culture of measuring instruments and devices, and the culture solution around them It is important to avoid contact with etc. as much as possible. Therefore, in order to automate the culture of cells and tissues for the purpose of regenerative medicine, it is necessary to measure and diagnose the degree of differentiation of cells and tissues in culture in a non-contact, non-destructive, or non-invasive manner. Become.
Therefore, as a conventional diagnosis of the degree of differentiation of cells, a method of diagnosing the degree of differentiation is proposed by transplanting cells for the purpose of diagnosing the degree of differentiation into an experimental animal such as a mouse and observing the progress after transplantation. (For example, Patent Document 3). In addition, a method for diagnosing the degree of differentiation of cells by measuring the amount of a specific protein expressed on the cell surface depending on the differentiation state of cells or tissues, or the degree of expression of a specific gene expressed depending on the differentiation state A method of diagnosing the degree of differentiation of cells by analyzing the above has been proposed (for example, Patent Documents 4 and 5).
However, according to the method described in Patent Document 3 described above, a skilled technique of a certain level or more is required for efficiently transplanting cells or tissues into an experimental animal, automation is difficult, and experimental results can be obtained. It takes a long time of several weeks to several months, and during that time, there was a problem that cells and tissues were killed or deteriorated.
Further, in the method for measuring the amount of protein described in Patent Document 4, an automatic device has not been developed, and the measured cells and tissues should be transplanted to a patient from the viewpoint of safety. It was necessary to destroy a large number of cells and tissues for the purpose of measurement. Further, even the method for analyzing the expression level of the gene described in Patent Document 5 has a problem that the analysis requires at least 2 to 3 days, and it is necessary to destroy a large number of cells for the purpose of the analysis.
Therefore, the present invention, from the background as described above, solves the conventional problems, non-destructive, and, non-invasively, the problem is to be able to automatically diagnose the degree of differentiation of cells in a short time, of the new cells An automatic diagnosis method of differentiation degree is provided.
本発明は、上記の課題を解決する手段として、細胞の分化を自動診断する方法として、第１には、細胞分化による細胞の形態変化を観察手段で観察し、得られた観察データを基に、細胞の形態変化を形態変化度として数値化して、細胞の分化度を診断することを特徴としている。
また、本発明は、第２には、観察データは、１個以上の細胞から計測される面積値および長径値のうち、少なくともいずれかの値を有することを特徴とし、第３には、上記第２の発明において、面積値および長径値の両者を有する観察データを基に次式（１）
から、長径短径面積比を算出し、この長径短径面積比から細胞の分化度を診断することを特徴としている。
さらに、第４には、細胞が幹細胞であって、幹細胞からの分化度を診断することを特徴とし、第５には、幹細胞が間葉系幹細胞であって、間葉系幹細胞からの分化度を診断することを特徴とし、そして、第６には、間葉系幹細胞からの分化度が、軟骨細胞への分化度であることを特徴としている。
さらにまた、第７には、長径短径面積比Ｘが、特定の閾値以上の細胞の割合から分化度を診断することを特徴とし、第８には、長径短径面積比Ｘが特定の閾値以上で、かつ、面積値Ａが特定の閾値以上である細胞の割合から分化度を診断することを特徴とする。
ここで、本発明は、間葉系幹細胞から軟骨細胞への分化度の診断においては、第９には、長径短径面積比Ｘの特定閾値が、０．２から０．４の範囲である細胞の割合から分化度を診断することを特徴とし、第１０には、長径短径面積比Ｘの特定閾値が０．２から０．４の範囲であり、かつ、面積値Ａの特定閾値が３０００から５０００μｍ２である細胞の割合から分化度を診断することを特徴としている。
また、本発明は、細胞を自動診断する装置として、第１１には、少なくとも細胞分化による細胞の形態変化を観察する観察手段、観察手段で得られた観察データを基に、細胞の形態変化を形態変化度として数値化する観察データ処理手段、および観察データ処理手段で得られた処理結果を出力する出力手段を備えていることを特徴とすし、第１２には、観察手段は、１個以上の細胞から計測される面積値および長径値のうち少なくともいずれかを観察データとして観察するものであることを特徴とし、第１３には、観察データ処理手段は、前記観察データを基に次式（１）
から長径短径面積比を算出し、この長径短径面積比から細胞の形態変化度を数値化するものであることを特徴とし、さらに、第１４には、診断対象となる細胞の数値化した形態変化度を、分化前の細胞における形態変化度と分化度を蓄積した第１データベースおよび分化移行時または分化完了後の細胞における形態変化度と分化度を蓄積した第２データベースそれぞれと対比して、細胞の分化度を診断する対比手段を有していることを特徴としている。
さらにまた、本発明は、第１５には細胞の自動培養装置として、少なくとも細胞を培養するためのインキュベーター、培養液の供給装置と排出装置、細胞の培養状態を観察する観察手段、および培養容器を連続的もしくは断続的に作動させる作動装置を有している細胞の自動培養装置において、上記第１１から第１４いずれかの細胞の分化度自動診断装置をも備えていることを特徴としている。
そして、上記第１の発明によれば、非破壊的、かつ、非侵襲的に、しかも短時間で細胞の分化度を自動診断できる。
第２の発明によれば、上記第１の発明の効果に加え、分化度の診断精度を向上させることができる。
第３の発明によれば、上記第２の発明の効果において、さらに分化度の診断精度を向上させることができる。
第４の発明によれば、上記第１から第３の発明の効果に加え、幹細胞からの分化度について、さらに効率よく診断できる。
第５の発明よれば、上記第４の発明の効果において、間葉系幹細胞からの分化度について、さらに効率よく診断できる。
第６の発明によれば、上記第５の発明の効果において、軟骨細胞への分化度について、さらに効率よく診断できる。
第７から第１０の発明によれば、上記第３から第６の発明の効果において、さらに効率よく各種の細胞の分化度を診断することができる。
さらに、第１１から第１４の発明によれば、使用者を問わず、上記第１から１０の発明の効果を効率よく得ることができる。
そして、第１５の発明によれば、細胞を自動培養できるとともに、上記第１１から第１４の効果をも発揮することができる。The present invention, as a means for solving the above-mentioned problems, is a method for automatically diagnosing cell differentiation. Firstly, the morphological change of cells due to cell differentiation is observed by an observing means, and based on the obtained observation data. The method is characterized by quantifying the morphological change of cells as the degree of morphological change to diagnose the degree of differentiation of cells.
The present invention is secondly characterized in that the observation data has at least one of an area value and a major axis value measured from one or more cells, and thirdly, the above. In the second invention, the following formula (1) is used based on the observation data having both the area value and the major axis value.
From this, the major axis/minor axis area ratio is calculated, and the degree of cell differentiation is diagnosed from this major axis/minor axis area ratio.
Further, the fourth is that the cells are stem cells and the degree of differentiation from the stem cells is diagnosed. The fifth is that the stem cells are mesenchymal stem cells and the degree of differentiation from the mesenchymal stem cells is And sixthly, the degree of differentiation from mesenchymal stem cells is the degree of differentiation into chondrocytes.
Furthermore, the seventh feature is that the degree of differentiation of the major axis and minor axis area X is diagnosed from the ratio of cells having a specific threshold value or more, and the eighth aspect is that the major axis and minor axis area ratio X is a specific threshold value. This is characterized in that the degree of differentiation is diagnosed from the ratio of cells whose area value A is equal to or greater than a specific threshold value.
Here, in the present invention, in the diagnosis of the degree of differentiation of mesenchymal stem cells into chondrocytes, ninthly, the specific threshold value of the major axis/minor axis area ratio X is in the range of 0.2 to 0.4. Characterized by diagnosing the degree of differentiation from the ratio of cells, tenthly, the specific threshold value of the major axis/minor axis area ratio X is in the range of 0.2 to 0.4, and the specific threshold value of the area value A is It is characterized in that the degree of differentiation is diagnosed from the ratio of cells having a size of 3000 to 5000 μm 2 .
In addition, the present invention provides, as an apparatus for automatically diagnosing cells, eleventhly, an observing means for observing at least a morphological change of cells due to cell differentiation, and a morphological change of cells based on observation data obtained by the observing means. It is characterized in that it is provided with an observation data processing means for digitizing the degree of morphology change and an output means for outputting a processing result obtained by the observation data processing means. Twelfth, at least one observation means is provided. The observation data processing means is characterized by observing at least one of an area value and a major axis value measured from the cells as observation data. 1)
It is characterized in that the ratio of major axis to minor axis is calculated from the ratio of major axis to minor axis, and the degree of morphological change of cells is quantified from this ratio of major axis to minor axis. The degree of morphological change is compared with the first database that stores the degree of morphological change and the degree of differentiation in cells before differentiation and the second database that accumulates the degree of morphological change and the degree of differentiation in cells during or after the transition to differentiation. It is characterized by having a comparison means for diagnosing the degree of differentiation of cells.
Furthermore, the present invention fifteenthly, as an automatic cell culture device, at least an incubator for culturing cells, a supply device and a discharge device of a culture solution, an observation means for observing the culture state of cells, and a culture container. An automatic cell culture device having an operating device that operates continuously or intermittently is characterized in that it is also provided with an automatic diagnostic device for the degree of differentiation of any one of the eleventh to fourteenth cells.
According to the first aspect of the present invention, the degree of cell differentiation can be automatically diagnosed nondestructively and noninvasively in a short time.
According to the second invention, in addition to the effect of the first invention, it is possible to improve the diagnostic accuracy of the degree of differentiation.
According to the third invention, in addition to the effects of the second invention, it is possible to further improve the diagnostic accuracy of the degree of differentiation.
According to the fourth invention, in addition to the effects of the first to third inventions, the degree of differentiation from stem cells can be more efficiently diagnosed.
According to the fifth invention, in the effect of the fourth invention, the degree of differentiation from mesenchymal stem cells can be more efficiently diagnosed.
According to the sixth invention, in the effect of the fifth invention, the degree of differentiation into chondrocytes can be more efficiently diagnosed.
According to the seventh to tenth inventions, in the effects of the third to sixth inventions, it is possible to more efficiently diagnose the degree of differentiation of various cells.
Further, according to the eleventh to fourteenth inventions, the effects of the first to tenth inventions can be efficiently obtained regardless of the user.
Then, according to the fifteenth invention, the cells can be automatically cultured, and the eleventh to fourteenth effects can be exhibited.
図１は、本発明における細胞培養から細胞の分化度診断までのフローチャートを例示した概略図である。
図２は、骨髄間葉系幹細胞から軟骨細胞への分化誘導培養における観察結果を示した図であり、（Ａ）は培養１日目、（Ｂ）培養２日目、（Ｃ）培養４日目である。
図３は、コントロール培養における観察結果を示した図であり、（Ａ）は培養１日目、（Ｂ）培養２日目、（Ｃ）培養４日目である。FIG. 1 is a schematic diagram exemplifying a flowchart from cell culture to diagnosis of cell differentiation in the present invention.
FIG. 2 is a view showing the observation results in the culture inducing differentiation of bone marrow mesenchymal stem cells into chondrocytes, where (A) is the first day of culture, (B) the second day of culture, and (C) the fourth day of culture. It's an eye.
FIG. 3 is a view showing the observation results in the control culture, (A) shows the first day of culture, (B) the second day of culture, and (C) the fourth day of culture.
本発明は上記のとおりの特徴をもつものであるが、以下にその実施の形態について詳しく説明する。
本発明の細胞の分化度自動診断方法は、たとえば、閉鎖された無菌状態の内部空間を有する箱体の培養装置内で、培養容器において各種の細胞もしくは組織を培養する自動培養装置を適用することで、効率よく細胞の分化度を、細胞の数や面積、長径、大きさ等から、細胞の形状変化を定量化して測定でき、非破壊的、かつ、非侵襲的に、しかも短時間で自動診断することができる。したがって、通常、この自動培養装置の箱体には、たとえば、細胞を培養するインキュベーター、培養液の供給装置と排出装置、細胞の培養状態の観察手段（観察装置）ならびに、これら観察手段に培養容器を連続的もしくは断続的に作動、移動させる作動装置が配置されている。また、培養状態の観察手段からのデータ信号（観察データ）によって、前記の観察手段の少なくとも、いずれかのものの動作を電気信号により指示制御する指示制御装置等が備えられている。
すなわち、本発明においては、少なくとも細胞の分化度を自動診断するための手段：
＜１＞培養中もしくは培養終了の細胞における細胞分化による細胞の形態変化を観察する観察手段；
＜２＞この観察手段で得られた観察データを基に、細胞の形態変化を形態変化度として数値化処理する観察データ処理手段；および
＜３＞この観察データ処理手段で得られた処理結果を出力する、モニター等の出力手段；
を備えている細胞の分化度自動診断装置も提供し、さらに＜４＞診断対象の細胞の形態変化度と、すでにデータベース化、すなわち、分化前の細胞の形態変化度と分化度が蓄積されている第１データベース（以下、ＤＢ１とする）および分化移行時または分化完了時の細胞の形態変化度と分化度が蓄積されている第２データベース（以下、ＤＢ２とする）それぞれと対比して、検量線等を算出することで、細胞の分化度を診断することのできる対比手段をも有する提供するとともに、このような細胞の分化度自動診断装置を、細胞の自動培養装置に適用することで、細胞の分化度を自動診断をも可能とした自動培養装置をも提供することができる。
ここで、本発明の分化度自動診断方法を適用することのできる培養装置としては、特に限定されないが、たとえば、本発明者が開発した、生体由来の細胞や組織を自動で培養することのできる自動培養装置等、各種の培養装置に適用することができる。なお、前記自動培養装置の構成としては、たとえば、閉鎖され、かつ、無菌状態の培養装置内で細胞または組織の培養の一連の培養操作および各種の培養環境制御を自動化した培養装置であって、培養装置内が複数の空間に区分けされていたり、また、細胞や組織等の培養物に対して、非侵襲的に培養物の特性や状態等を測定でき、かつ、これら一連の測定作業を自動化されていてもよい。
本発明の細胞の分化度自動診断方法等における「自動診断」としては、上記のような構成を有する自動培養装置を利用して、対象となる細胞（もしくは組織）、培養容器を作業者等の人手で操作するだけでなく、効率よく細胞の分化度の診断結果を得ることができ、そして、たとえば、後述するＣＣＤカメラ等の観察手段からの吸光度等の１次的に得られる測定値や画像データ等を含む観察データを基にした分化度の診断結果（診断値）を、コンピュータ等で演算、計算する機能を備え、また、得られた診断結果を出力する出力手段、例えば、モニター等を備えていてもよい。
本発明の細胞の分化度自動診断方法等でいう「非破壊的」な診断とは、細胞や組織を生存させたまま細胞の分化度を診断することであり、たとえば、光学顕微鏡等による非接触的な観察方法が挙げられる。また、「非侵襲的」な診断とは、細胞や組織に薬剤等を投与すること等の化学的な影響を与えることなく診断することであり、たとえば、細胞が本来有している蛍光物質の蛍光観察等が挙げられる。
つづいて、本発明の細胞の分化度自動診断方法について説明する。まず、細胞や組織の分化による細胞や組織の形態変化を、たとえば、倒立顕微鏡、蛍光顕微鏡、レーザー共焦点顕微鏡等の光学顕微鏡、原子間力顕微鏡、分子間力顕微鏡、レーザー変位計、さらにはＣＣＤカメラ等の観察機器等をはじめとした各種の観察手段で観察する。そして、これら観察手段で得られた観察データ（顕微鏡観察画像）を基に、細胞や組織の形態変化を「形態変化度」としてコンピュータ等で計算して数値化することを特徴としている。
このとき、本発明の細胞の分化度自動診断方法における「観察データ」は、１個以上の細胞から計測される面積値および長径値のうち、少なくともいずれかの値を有することを特徴としている。つまり、まず「面積値」について説明すると、「面積値」とは、たとえば、細胞（もしくは、組織）の接着面に対する細胞の投影面積、あるいは、細胞（もしくは、組織）の外表面積等であり、観察データとしてコンピュータ等を利用して計算することができる。また、「長径値」とは、たとえば、細胞（もしくは、組織）の画像外周部の最も離れた点の間の距離を意味し、「面積値」と同様に、観察データとしてコンピュータ等を利用して計算することができる。そして、さらに具体的に説明すると、細胞の分化度をより効率よく診断するために、これら「面積値」および「長径値」の両者の値を有する観察データを基に、次式（１）
から、長径短径面積比として算出し、この長径短径面積比から細胞の分化度を効率よく診断することができる。つまり、この長径短径面積比は、細胞や組織の形態変化の度合いである形態変化度に相当し、ひいては、細胞の分化度に相当するものである。これは、「形態変化度と分化度は、相関する」という、本発明者の鋭意研究の結果である新規の知見に基づいているものである。また、この長径短径面積比は、長径と短径の比に関係する細胞形状を代表するパラメーターであると位置付けることができる。
なお、この観察データについては、上記のとおり各種の観察手段で得られたものであり、細胞の形状に関する２次元的、または３次元的、もしくは時間変化を含めた４次元的なデータ等を例示することができる。
すなわち、本発明の細胞の分化度自動診断方法における「細胞の形態変化（形態変化度）」は、たとえば、繊維芽状、多角形状、円形状、球形状等の形状変化の度合いをはじめ、細胞の外周辺の内角の度数、面積、細胞外周の対角線の本数、対角線の内で最長のものの長さ、細胞の接着面からの最高の高さ、細胞の体積、細胞の体積を細胞の接着面積で割った値、これらの値の経時変化の速度等から求めることができる。
本発明の細胞の分化度自動診断方法における「分化度」についても説明する。「分化度」とは、細胞の分化の程度（度合い）を定量的もしくは半定量的に表す数値である。たとえば、＜１＞細胞の分化に応じて発現される細胞表面タンパク質の絶対的な量もしくは相対的な量、＜２＞細胞の分化に応じて発現される遺伝子に対応するｍＲＮＡ（メッセンジャーＲＮＡ）の絶対的な量もしくは相対的な量、＜３＞細胞の分化に応じて変化する細胞酵素の活性の絶対的な量もしくは相対的な量、さらに＜４＞細胞の分化に応じてその生産量が変化するタンパク質等の代謝物の絶対的な量もしくは相対的な量等がある。特に本発明における分化度は、ある培養器内の全ての細胞の分化度の平均値として得られてもよいし、あるいは、単一の細胞の値として得られてもよい。
そして、本発明の細胞の分化度自動診断方法の流れとしては、図１に例示したように、診断対象となる細胞を培養し、培養した細胞の培養状態を観察するとともに、細胞形態から細胞の形態変化を観察し、得られた観察結果（観察データ）を形態変化度として数値化処理し、この数値化した形態変化度から細胞の分化度を診断する。さらに説明すると、図１の例のように、例えば、細胞の分化の度合いを定量化する上記＜１＞〜＜４＞等で得られる結果を基に、細胞の分化前を示す値を特定し、この値と分化前の細胞を観察して得られた観察データを基にして数値化した形態変化度とを関連付けして閾値として特定し、また、細胞の分化移行もしくは分化完了を示す値を特定し、この値と分化移行時の細胞形状または分化完了時の細胞形状の観察データから数値化した形態変化度とを関連付けて閾値として特定し、これら閾値データそれぞれをＤＢ１、ＤＢ２として蓄積しておくことで、次回から細胞の形状を観察して、観察データから形態変化度を取得し、データベース化した閾値と対比させることで、各種の細胞の分化度を自動診断することができる。
さらに説明すると、長径短径面積比Ｘが、ある特定の閾値以上の細胞の割合から、細胞の分化度を診断することができ、また、長径短径面積比Ｘがある特定の閾値以上で、かつ、面積値Ａが別のある特定の閾値以上である細胞の割合からも、細胞の分化度を診断することができる。なお、長径短径面積比Ｘおよび面積値Ａ「特定の閾値」とは、細胞の種類によって異なる。
この長径短径面積比Ｘおよび面積値Ａについて、間葉系幹細胞を例に挙げてさらに説明すると、間葉系幹細胞は典型的な繊維芽状、すなわち細長い菱形の針の様な形態を示すことはよく知られており、間葉系幹細胞はその接着面積も長さの割には小さい。このことから、間葉系幹細胞の長径短径面積比Ｘの値は比較的小さい。これに対して、軟骨組織中の軟骨細胞は一般に丸い形態をとっており、その長径短径面積比Ｘの値は大きく、接着面積の面積値Ａに相当する投影面積は比較的大きい。
本発明で扱う軟骨細胞は、このような軟骨組織中の軟骨細胞ではなく、体外で培養されている状態の軟骨細胞であるため、間葉系幹細胞から分化した軟骨細胞の長径短径面積比Ｘや、接着面積の面積値Ａが大きくなる直接の理由は不明であるが、軟骨組織中の軟骨細胞の形態に近づくゆえに長径短径面積比Ｘや面積値Ａが大きくなると考えることができる。
また、軟骨細胞は細胞外に多量の細胞外タンパク質（例えば、ＩＩコラーゲンやアグリカン等）を分泌蓄積するという特徴を有していることから、分化により生じた軟骨細胞が多量の細胞外タンパク質を自身の周囲に分泌し、その細胞外タンパク質の層の上に軟骨細胞自身が接着し、伸展できる。このため、結果として軟骨細胞の形態が、細長い繊維芽状態から比較的丸に近い、すなわち、長径短径面積比Ｘが大きい形態となり、また周囲に豊富に分布せしめた細胞外タンパク質に接着することから軟骨細胞の面積値Ａも大きくなる。
したがって、種々の細胞の分化、例えば、間葉系幹細胞から軟骨細胞へと分化中の細胞群の中で長径短径面積比Ｘがある特定の閾値以上、例えば、０．２から０．４の範囲である細胞や、面積値Ａがある特定の閾値以上、例えば、３０００から５０００μｍ２の細胞、さらには長径短径面積比Ｘが上記のとおりの特定閾値以上で、かつ、面積値Ａが別の上記のとおりの特定閾値以上である細胞が、軟骨細胞への分化が進んだ、あるいは、終了した細胞であると十分に考えることができ、軟骨細胞とて認識、判断することができる。
本発明の細胞の分化度自動診断方法は、このような細胞の分化度を、細胞の形態変化度、すなわち、細胞の数や面積、長径、大きさ等の形状変化の定量化して測定することで、簡単に、診断することができる。
次に、本発明の細胞の分化度自動診断方法が対象としうる「細胞（もしくは、組織）」について説明すると、その由来は、たとえば植物、昆虫および動物等であり、特に動物としては鳥類、爬虫類、両生類、魚類、哺乳類等が挙げられる。さらに、哺乳類としては、ヒト、サル、ブタ、ウシ、ヒツジ、ネズミ、ウマ等が例示できる。
そして、本発明の細胞の分化度自動診断方法は、再生医療の発展に大きく貢献し、活用し得るものであることを考慮すると、細胞（もしくは組織）の由来は、ヒトであることが好ましい。さらに、ヒト由来の細胞の中でも、免疫拒絶反応を回避することやより効果的に患者に馴化させるという観点から、患者自身を由来とする自家細胞であることがさらに好ましい。もちろん、本発明の細胞の分化度自動診断方法は、他家細胞に対しても適用することができる。
また、細胞としては、幹細胞をも対象とすることができる。「幹細胞」としては、たとえば、胚性幹細胞、生殖幹細胞、神経幹細胞、肝幹細胞、造血幹細胞、間葉系幹細胞等を対象として、これら細胞の分化度を診断することができる。特に、間葉系幹細胞からの分化度としては、軟骨細胞への分化度への診断を効率よく行うことができる。なお、この「間葉系幹細胞」とは、軟骨、骨、脂肪等をはじめとした間葉系の組織、細胞に分化する能力を有する細胞であり、骨髄液中に存在する骨髄間葉系幹細胞がその代表的な例としてあげることができる。特に、軟骨細胞は、手足の関節軟骨、鼻、耳等の軟骨組織を形成している細胞であり、硝子軟骨細胞や繊維軟骨細胞等が例示でき、本発明の細胞の分化度自動診断方法を利用して、間葉系幹細胞から軟骨細胞への分化度を診断することで、このような軟骨組織を効率よく培養することができる。
さらに、細胞とコラーゲンゲル膜、繭糸、マイクロチップやナイロンメッシュ等の非細胞との融合細胞も対象とすることができる。
もちろん、初代細胞や株化細胞でもよい。初代細胞としては、たとえば、ヒト初代臍帯血細胞、ヒト初代骨髄細胞、ヒト初代神経細胞、ヒト初代心筋細胞、ヒト初代肝細胞、ヒト初代造血細胞、ヒト初代軟骨細胞、ヒト初代間葉系細胞等が例示される。また、株化細胞としては、ヒト子宮ガン由来のＨｅＬａ細胞、ヒト肝ガン由来のＨｕｈ７細胞等が例示できる。また、これら細胞にプラスミド導入やウイルス感染等の遺伝子操作により得られた細胞もこの出願の発明に用いることができる。なお、「初代細胞」とは、一般に生体から細胞を採取して、５０回程度の限られた回数のみ増殖および分裂する細胞を指し、「株化細胞」は、生体から細胞を採取した後も、５０回以上の増殖および分裂する細胞のことをいう。
一方、「組織」とは、たとえば肝臓、心臓、腎臓、皮膚、骨、軟骨、骨髄等や、これら例示した組織から派生して形成された組織等が挙げられる。
そして、これら細胞を培養する際、任意の種類の細胞または組織を得るため、分化を促進させる因子として分化誘導因子と呼ばれる薬剤を用いることもあるが、この種々の分化誘導因子の中から、最も適した分化誘導因子を用いるには、分化前の細胞の種類と分化後に得られる細胞の種類に依存する。また、単独あるいは複数の分化誘導因子の利用が可能である。これら分化誘導因子として、赤血球細胞に分化誘導させるエリスロポエチン、骨芽細胞への分化誘導を促進させるｂｏｎｅ ｍｏｒｐｈｏｇｅｎｉｃ ｐｒｏｔｅｉｎ（ＢＭＰ）、肝実質細胞等への分化誘導を行うｈｅｐａｔｏｃｙｔｅ ｇｒｏｗｔｈ ｆａｃｔｏｒ（ＨＧＦ）、軟骨細胞へ分化を促進させるｔｕｍｏｒ ｇｒｏｗｔｈ ｆａｃｔｏｒ−β（ＴＧＦ−β）等が例示できる。
これら分化誘導因子は、本発明の細胞の分化度自動診断方法によって得られた分化度の診断結果を基に、適宜にその使用量を効率よく調節することができる。
本発明に用いることができる「培養容器」については、その素材はいかなるものでもよく、たとえばプラスチック製、ガラス製等がある。具体的には、たとえば、プラスチックの素材としては、セルロース等の天然繊維、ポリスチレン、ポリスルフォン、ポリカーボネイト等の合成化合物およびこれらを組み合わせた混合物等がある。また、ポリ乳酸、ポリグリクロン酸等のような生体吸収性または生体分解高分子を用いてもよい。さらに、これらプラスチック素材をコラーゲン、ゼラチン、フィブロネクチン等の天然細胞外マトリックスやエチレンビニルアルコール共重合体等の人工化合物によりコーティングし親水化させて、培養容器として利用してもよい。ジエチルアミン、ジエチルアミノエチル等により修飾したものやプラズマ放電処理等を施し、表面に荷電基を導入したものも利用できる。
このような培養容器は、一般の研究室や実験室で使用されることを主な目的として設計されて市販されているものでもよく、その内容積は一般的には１００μＬ〜５００ｍＬであるが、大量培養用の培養容器を使用することもできる。また、培養容器内に細胞や組織を接着や固定をする担体を含ませた培養容器も利用できる。この場合の担体としては、不織布、織物、ゲル、発泡体、繭糸、針金、凍結乾燥された多孔体等が例示できる。さらにまた、培養容器内での物質の移動阻害、促進、選択あるいは細胞の接着等を目的とした限外濾過膜、精密濾過膜、逆浸透膜等のような膜を内部に含ませた培養容器を使用することもできる。
また、培養容器の形状は、受け皿部と蓋部とからなるディッシュ型、液体等を出し入れする開口部が一つまたは複数備えたフラスコ型が例示できる。ディッシュ型の培養容器において、ディッシュ内が複数に区分けされたマルチウェル型やフラスコ型の培養器において、内面の全部または一部がガス透過性を有する多孔質膜からなるものもあり、これらも当然に使用することができる。
以下に実施例を示して、本発明についてさらに具体的に説明するが、本発明はこの例によって限定されるものではない。The present invention has the characteristics as described above, and the embodiments thereof will be described in detail below.
The method for automatically diagnosing the degree of differentiation of cells of the present invention is, for example, to apply an automatic culturing apparatus for culturing various cells or tissues in a culturing container in a culturing apparatus having a box having a closed and sterile internal space. The cell differentiation rate can be efficiently quantified and measured based on the number, area, major axis, size, etc. of cells, which is non-destructive, non-invasive, and automatic in a short time. Can be diagnosed. Therefore, in general, the box of the automatic culture device includes, for example, an incubator for culturing cells, a supply device and a discharge device for a culture solution, an observation means (observation device) for culturing cells, and a culture container for these observation means. An operating device is arranged to operate or move the device continuously or intermittently. Further, there is provided an instruction control device or the like for instructing and controlling the operation of at least one of the observation means by an electric signal in response to a data signal (observation data) from the culture state observation means.
That is, in the present invention, at least means for automatically diagnosing the degree of differentiation of cells:
<1> Observation means for observing cell morphological changes due to cell differentiation in cells during or after culture;
<2> An observation data processing unit that digitizes a cell morphological change as a morphological change degree based on the observation data obtained by this observing unit; and <3> a processing result obtained by this observation data processing unit. Output means for outputting, such as a monitor;
Also provided is an automatic diagnostic apparatus for the degree of differentiation of cells, which further comprises <4> a degree of morphological change of cells to be diagnosed and a database, that is, the degree of morphological change of cells before differentiation and the degree of differentiation are accumulated. Calibration in comparison with a first database (hereinafter referred to as DB1) and a second database (hereinafter referred to as DB2) in which the degree of morphological change and the degree of differentiation of cells at the time of transition to differentiation or completion of differentiation are accumulated. By providing a comparison means that can be used to diagnose the degree of differentiation of cells by calculating the line, etc., by applying such an automatic diagnostic device for the degree of differentiation of cells to an automatic cell culture device, It is also possible to provide an automatic culture device that enables automatic diagnosis of the degree of cell differentiation.
Here, the culture apparatus to which the method for automatically diagnosing the degree of differentiation of the present invention can be applied is not particularly limited, but, for example, cells and tissues derived from a living organism, developed by the present inventor, can be automatically cultured. It can be applied to various culture devices such as an automatic culture device. The configuration of the automatic culture device, for example, a culture device that is closed, and that automates a series of culture operations for culturing cells or tissues in the culture device in a sterile state and various culture environment controls, The inside of the culture device is divided into multiple spaces, and the characteristics and state of the culture can be measured non-invasively to the culture of cells and tissues, and these series of measurement operations are automated. It may have been done.
As the "automatic diagnosis" in the method for automatically diagnosing the degree of differentiation of cells of the present invention, the target cell (or tissue) and the culture container can be used by an operator or the like by using the automatic culture device having the above-mentioned configuration. Not only is it manually operated, but it is possible to efficiently obtain a diagnostic result of the degree of differentiation of cells, and for example, a measurement value or an image obtained primarily from an observation means such as a CCD camera, which will be described later, or an image obtained. The computer has a function to calculate and calculate the diagnostic result (diagnostic value) of the differentiation degree based on the observation data including the data, and output means such as a monitor for outputting the obtained diagnostic result. You may have it.
The "non-destructive" diagnosis referred to in the method for automatically diagnosing the degree of differentiation of cells of the present invention means diagnosing the degree of differentiation of cells while keeping cells and tissues alive, and for example, non-contact with an optical microscope or the like. Observing method. Further, the "non-invasive" diagnosis is to make a diagnosis without exerting a chemical influence such as administering a drug or the like to cells or tissues, and for example, to detect a fluorescent substance originally possessed by cells. Examples include fluorescence observation.
Next, the method for automatically diagnosing the degree of differentiation of cells of the present invention will be described. First, the morphological changes of cells and tissues due to the differentiation of cells and tissues are analyzed by, for example, an optical microscope such as an inverted microscope, a fluorescence microscope, a laser confocal microscope, an atomic force microscope, an intermolecular force microscope, a laser displacement meter, and a CCD. Observation is performed by various observation means such as an observation device such as a camera. Then, based on the observation data (microscopic observation image) obtained by these observing means, the morphological change of cells and tissues is calculated as a “morphological change degree” by a computer or the like and digitized.
At this time, the "observation data" in the method for automatically diagnosing the degree of differentiation of cells of the present invention is characterized by having at least one of an area value and a major axis value measured from one or more cells. That is, first, the “area value” will be described. The “area value” is, for example, the projected area of the cell on the adhesion surface of the cell (or tissue), or the outer surface area of the cell (or tissue), The observation data can be calculated using a computer or the like. Further, the “major axis value” means, for example, the distance between the most distant points on the outer peripheral portion of the image of a cell (or tissue), and like the “area value”, a computer or the like is used as observation data. Can be calculated. Then, more specifically, in order to more efficiently diagnose the degree of differentiation of cells, the following formula (1) is used based on the observation data having both the values of “area value” and “major axis value”.
From the above, it is calculated as the major axis/minor axis area ratio, and the degree of differentiation of cells can be efficiently diagnosed from this major axis/minor axis area ratio. That is, this major axis/minor axis area ratio corresponds to the degree of morphological change, which is the degree of morphological change of cells or tissues, and thus to the degree of differentiation of cells. This is based on a new finding, which is a result of the inventor's earnest research that "the degree of morphological change and the degree of differentiation are correlated". Further, this major axis/minor axis area ratio can be regarded as a parameter representing the cell shape related to the ratio of major axis and minor axis.
It should be noted that this observation data is obtained by various observation means as described above, and is exemplified by two-dimensional or three-dimensional data regarding the shape of cells, or four-dimensional data including temporal changes. can do.
That is, the “cell morphological change (morphological change)” in the method for automatically diagnosing the degree of differentiation of cells of the present invention includes, for example, the degree of shape change such as fibroblast, polygon, circle, sphere, and the like. The number of inner angles around the outer periphery of the cell, the area, the number of diagonal lines around the cell periphery, the length of the longest diagonal line, the maximum height from the cell's adhesive surface, the volume of the cell, and the volume of the cell It can be determined from the values divided by, the speed of change of these values with time, and the like.
The "differentiation degree" in the method for automatically diagnosing the differentiation degree of cells of the present invention will also be described. The “differentiation degree” is a numerical value that quantitatively or semi-quantitatively represents the degree (degree) of cell differentiation. For example, <1> absolute or relative amount of cell surface protein expressed in response to cell differentiation, <2> mRNA (messenger RNA) corresponding to a gene expressed in response to cell differentiation, Absolute amount or relative amount, <3> Absolute amount or relative amount of cellular enzyme activity that changes according to cell differentiation, and <4> Production amount according to cell differentiation There are absolute or relative amounts of changing metabolites such as proteins. In particular, the degree of differentiation in the present invention may be obtained as an average value of the degrees of differentiation of all cells in a certain incubator, or may be obtained as the value of a single cell.
The flow of the method for automatically diagnosing cell differentiation of the present invention includes, as illustrated in FIG. 1, culturing cells to be diagnosed, observing the culture state of the cultivated cells, The morphological change is observed, the obtained observation result (observation data) is digitized as the morphological change degree, and the differentiation degree of the cell is diagnosed from the digitized morphological change degree. To further explain, as in the example of FIG. 1, for example, based on the results obtained in the above <1> to <4> for quantifying the degree of differentiation of cells, the value indicating the pre-differentiation of cells is specified. , This value and the degree of morphological change quantified based on the observation data obtained by observing the cells before differentiation are associated and specified as a threshold value. This value is associated with the morphological change degree quantified from the observation data of the cell shape at the time of differentiation transition or the cell shape at the time of differentiation completion, and specified as a threshold value, and these threshold value data are accumulated as DB1 and DB2, respectively. By setting the cell shape, it is possible to automatically diagnose the degree of differentiation of various cells by observing the cell shape from the next time, acquiring the degree of morphological change from the observation data, and comparing it with the threshold value stored in the database.
Explaining further, the degree of differentiation of cells can be diagnosed from the ratio of cells in which the major axis/minor axis area ratio X is a certain threshold value or more, and the major axis/minor axis area ratio X is a certain threshold value or more, Moreover, the degree of differentiation of cells can be diagnosed also from the ratio of cells whose area value A is equal to or larger than another specific threshold value. The major axis/minor axis area ratio X and the area value A “specific threshold” differ depending on the cell type.
The major axis/minor axis area ratio X and the area value A will be further described by taking mesenchymal stem cells as an example. Mesenchymal stem cells show a typical fibroblast-like, ie, elongated rhombic needle-like morphology. Is well known, and mesenchymal stem cells have a small adhesion area for their length. Therefore, the mesenchymal stem cells have a relatively large major axis/minor axis area ratio X. On the other hand, the chondrocytes in the cartilage tissue generally have a round shape, the value of the major axis/minor axis area ratio X is large, and the projected area corresponding to the area value A of the adhesion area is relatively large.
The chondrocytes treated in the present invention are not such chondrocytes in the cartilage tissue but are chondrocytes in a state of being cultured in vitro. Therefore, the major axis/minor axis area ratio X of the chondrocytes differentiated from the mesenchymal stem cells is determined. The direct reason why the area value A of the adhesion area increases is unknown, but it can be considered that the major axis/minor axis area ratio X and the area value A increase because the shape of the chondrocytes in the cartilage tissue approaches.
In addition, since chondrocytes have the characteristic of secreting and accumulating a large amount of extracellular proteins (eg, II collagen, aggrecan, etc.) extracellularly, the chondrocytes generated by differentiation themselves produce a large amount of extracellular proteins. It is secreted to the surrounding area, and chondrocytes themselves adhere and spread on the extracellular protein layer. Therefore, as a result, the morphology of the chondrocytes becomes relatively round from the elongated fibroblast state, that is, the morphology of the major axis/minor axis area X is large, and adheres to extracellular proteins abundantly distributed in the periphery. Therefore, the area value A of chondrocytes also increases.
Therefore, in a cell group undergoing differentiation of various cells, for example, differentiation from mesenchymal stem cells to chondrocytes, the major axis/minor axis area ratio X is not less than a certain threshold value, for example, 0.2 to 0.4. The range of cells, the area value A is a certain threshold value or more, for example, the cells of 3000 to 5000 μm 2 , the major axis/minor axis area ratio X is the specific threshold value or more as described above, and the area value A is different. It is possible to fully consider that the cells having the specific threshold value or more as described above are cells that have been differentiated into chondrocytes or have been completed, and can be recognized and determined as chondrocytes.
The method for automatically diagnosing differentiation degree of cells of the present invention is to measure such differentiation degree of cells by quantifying the degree of morphological change of cells, that is, the number and area of cells, major axis, shape change such as size. So, you can easily diagnose.
Next, the “cell (or tissue)” that can be targeted by the method for automatically diagnosing the degree of differentiation of cells of the present invention will be described. The origin thereof is, for example, plants, insects, animals, etc., and particularly animals include birds and reptiles. , Amphibians, fish, mammals and the like. Furthermore, examples of mammals include humans, monkeys, pigs, cows, sheep, mice, horses, and the like.
Considering that the method for automatically diagnosing the degree of differentiation of cells of the present invention greatly contributes to the development of regenerative medicine and can be utilized, the origin of cells (or tissues) is preferably human. Furthermore, among human-derived cells, autologous cells derived from the patient themselves are more preferable from the viewpoint of avoiding immune rejection reaction and more effectively acclimatizing to the patient. Of course, the method for automatically diagnosing the degree of differentiation of cells of the present invention can also be applied to allogeneic cells.
In addition, stem cells can also be targeted as cells. As the “stem cells”, for example, embryonic stem cells, reproductive stem cells, neural stem cells, hepatic stem cells, hematopoietic stem cells, mesenchymal stem cells, etc. can be targeted and the degree of differentiation of these cells can be diagnosed. In particular, as the degree of differentiation from mesenchymal stem cells, the degree of differentiation into chondrocytes can be efficiently diagnosed. The “mesenchymal stem cells” are cells having the ability to differentiate into mesenchymal tissues and cells such as cartilage, bone, and fat, and bone marrow mesenchymal stem cells present in bone marrow fluid. Can be cited as a typical example. In particular, chondrocytes are cells that form cartilage tissues such as articular cartilage of limbs, nose, and ears, and can be exemplified by hyaline chondrocytes and fibrochondrocytes, etc. By utilizing this to diagnose the degree of differentiation of mesenchymal stem cells into chondrocytes, such cartilage tissue can be efficiently cultured.
Furthermore, fused cells of cells and non-cells such as collagen gel membranes, cocoon threads, microchips and nylon mesh can also be targeted.
Of course, it may be a primary cell or established cell line. As the primary cells, for example, human primary cord blood cells, human primary bone marrow cells, human primary neural cells, human primary cardiomyocytes, human primary hepatocytes, human primary hematopoietic cells, human primary chondrocytes, human primary mesenchymal cells, etc. It is illustrated. Examples of the established cell lines include human uterine cancer-derived HeLa cells and human liver cancer-derived Huh7 cells. Further, cells obtained by genetic manipulation such as plasmid introduction or virus infection into these cells can also be used in the invention of this application. The term "primary cell" generally refers to a cell that is collected from a living body and proliferates and divides only a limited number of times, such as about 50 times. , A cell that grows and divides 50 times or more.
On the other hand, examples of the "tissue" include liver, heart, kidney, skin, bone, cartilage, bone marrow, and the like, and tissues formed by deriving from these exemplified tissues.
Then, when culturing these cells, a drug called a differentiation inducing factor may be used as a factor for promoting differentiation in order to obtain cells or tissues of any kind, but among these various differentiation inducing factors, the most The use of a suitable differentiation inducer depends on the cell type before differentiation and the cell type obtained after differentiation. In addition, it is possible to use a single or a plurality of differentiation inducing factors. As these differentiation inducers, erythropoietin that induces differentiation into erythroid cells, bone morphogenic protein (BMP) that promotes induction of differentiation into osteoblasts, hepacytocyte growth factor (HGF) that induces differentiation into hepatocytes, chondrocytes, etc. Tumor growth factor-β (TGF-β) and the like that promote differentiation into can be exemplified.
The amount of these differentiation-inducing factors to be used can be appropriately and efficiently adjusted based on the result of diagnosis of the degree of differentiation obtained by the method for automatically diagnosing the degree of differentiation of cells of the present invention.
The "culture vessel" that can be used in the present invention may be made of any material, for example, plastic or glass. Specifically, for example, as a plastic material, there are natural fibers such as cellulose, synthetic compounds such as polystyrene, polysulfone, and polycarbonate, and mixtures thereof. In addition, bioabsorbable or biodegradable polymers such as polylactic acid and polyglycuronic acid may be used. Further, these plastic materials may be coated with a natural extracellular matrix such as collagen, gelatin, fibronectin or the like or an artificial compound such as ethylene vinyl alcohol copolymer to be hydrophilized to be used as a culture container. Those modified with diethylamine, diethylaminoethyl or the like, or those having a charged group introduced on the surface after plasma discharge treatment or the like can also be used.
Such a culture container may be designed and marketed mainly for use in general laboratories and laboratories, and the inner volume thereof is generally 100 μL to 500 mL, A culture container for large-scale culture can also be used. Further, a culture container in which a carrier for adhering or fixing cells or tissues is included in the culture container can also be used. Examples of the carrier in this case include non-woven fabric, woven fabric, gel, foam, cocoon thread, wire, freeze-dried porous body and the like. Furthermore, a culture container containing a membrane such as an ultrafiltration membrane, a microfiltration membrane, a reverse osmosis membrane, etc. for the purpose of inhibiting, promoting, selecting, or adhering cells in the movement of substances in the culture container. Can also be used.
Examples of the shape of the culture container include a dish type having a saucer portion and a lid portion, and a flask type having one or a plurality of openings through which liquids and the like are taken in and out. In a dish-type culture vessel, in a multi-well type or flask-type incubator in which the inside of the dish is divided into a plurality, some or all of the inner surface is made of a porous membrane having gas permeability, and these are naturally also Can be used for
Hereinafter, the present invention will be described more specifically with reference to examples, but the present invention is not limited to these examples.
１．骨髄間葉系幹細胞の採取と培養
インフォームドコンセントを経て、３人の健常人ボランティアの堆骨から、１３ｍｌづつ、骨髄液を採取した。この骨髄液中の有核細胞数を定法に従いチュルク液を用いて計数し、後述の培養培地を用いてそれぞれ細胞濃度が、６．０×１０５ｃｅｌｌｓ／ｃｍ２となるように、細胞培養用ディッシュ（コーニング社製：底面積５５ｃｍ２、培養液量１０ｍｌ）に播種し、３７℃、５％ＣＯ２濃度のインキュベーター内で静置培養した。
上記の培養培地としては、ＤＭＥＭ（ギブコ社製：型番号３１６００−３４）に１０％ウシ胎児血清（ギブコ社製：ロット番号２６１４０−０７９）を添加したものである。
培養開始から１日後および２日後に培地を交換し、浮遊細胞を除去したところ、いずれの培養でもディッシュ底面に接着細胞（骨髄間葉系幹細胞）が形成されていることを確認できた。その後、この接着細胞をコンフルエント近くまで増殖したのを顕微鏡で確認し、その１９日後に、全てのディッシュの接着細胞をトリプシン処理によりディッシュから剥離して、トリパンブルー液を用いて接着していた生細胞を計数した。これを、骨髄間葉系幹細胞として、次の培養に用いた。
２．軟骨細胞への分化誘導
上記１．にて培養して回収した骨髄間葉系幹細胞を、次の方法で軟骨細胞へ分化誘導した。なお、培養培地は、ＤＭＥＭ培地に分化誘導因子であるＴＧＦ−β３（１０ｎｇ／ｍｌ）とインシュリン様増殖因子（ＩＧＦ、１００ｎｇ／ｍｌ）を添加して分化誘導用培地として調製し、これを用いた。また、コントロール用培地としてＴＧＦ−β３とＩＧＦを添加しないＤＭＥＭ培地を調製して、この培地による培養も行った。
［１］ 骨髄間葉系幹細胞を、１００Φ培養ディッシュに、細胞密度が１×１０３ｃｅｌｌｓ／ｃｍ２となるように播種し、定法に従い１０日間培養した。
［２］ 上記［１］の培養の間、経時的に１００Φ培養ディッシュの底面に接着した骨髄間葉系幹細胞をトリプシン処理により剥離して、遠心分離機を利用して回収した。
［３］ 次に、回収した骨髄間葉系幹細胞を試料とし、リアルタイムＲＴ−ＰＣＲ法（リアルタイム逆転写ポリメラーゼ連鎖反応法）により軟骨細胞特有のタンパク質であるアグリカンのｍＲＮＡの発現量をアグリカン発現率（％）として確認し、骨髄間葉系幹細胞が軟骨細胞へと分化したことを確認した。なお、このとき初代ヒト軟骨細胞の発現量を１００％として指標とした。
［４］ 上記［３］のｍＲＮＡ発現量の確認の間、経時的に１００Φ培養ディッシュ内の細胞の形態変化についても、倒立顕微鏡で観察した。
［５］ この観察結果は、図２および図３に例示したとおりである。図２は、骨髄間葉系幹細胞から軟骨細胞への分化誘導培養における観察結果を示した図であり、（Ａ）は培養１日目、（Ｂ）培養２日目、（Ｃ）培養４日目である。図３は、コントロール培養における観察結果を示した図であり、（Ａ）は培養１日目、（Ｂ）培養２日目、（Ｃ）培養４日目である。
［６］ 図２に示した分化誘導培養では、図２（Ａ）に示したように細長い形状から、図２（Ｂ）および図２（Ｃ）と培養日数を追うごとに、多角形状に細胞の形態が変化していることが確認できた。一方、図３に示したコントロール培養では、細胞は、図３（Ａ）（Ｂ）（Ｃ）に示した何れの培養日数においても、その形状は細長いままであり、ほとんど変化しないことを確認した。
［７］ 次に、上記［６］で得られた顕微鏡画像による観察データを基に、コンピュータを利用して５０個の細胞の接着面に対する投影面積値（細胞面積値）と長径値を算出、計算し、得られた細胞面積値と長径値から次式（１）
から、長径短径面積比（つまり、細胞や組織の形態変化度に相当）を計算した。
３．細胞の形態変化度を基に、細胞の分化度の診断
そして、上記２．の［３］で確認したアグリカンのｍＲＮＡ発現量（アグリカン発現率（％））と、上記２．の［７］で計算した長径短径面積比（形態変化度）とを比較し、両者の相関関係について検討した。そして、その結果として、アグリカンのｍＲＮＡ発現量（アグリカン発現率（％））と長径短径面積比が、０．３以上の細胞の割合を表１に例示した。
もちろん、本発明は以上の例によって限定されるものではなく、その細部については様々な態様が可能であることはいうまでもない。1. Collection and culture of bone marrow mesenchymal stem cells After informed consent, 13 ml of bone marrow fluid was collected from the bone marrow of three healthy volunteers. The number of nucleated cells in this bone marrow fluid was counted using Turk's solution according to a standard method, and the cell concentration for cell culture was adjusted to 6.0×10 5 cells/cm 2 using the culture medium described later. It was seeded on a dish (manufactured by Corning: bottom area 55 cm 2 , culture solution amount 10 ml), and statically cultured at 37° C. in an incubator with a 5% CO 2 concentration.
As the above-mentioned culture medium, 10% fetal bovine serum (manufactured by Gibco: lot number 26140-079) was added to DMEM (manufactured by Gibco: model number 31600-34).
One day and two days after the start of the culture, the medium was exchanged and the floating cells were removed. As a result, it was confirmed that adherent cells (bone marrow mesenchymal stem cells) were formed on the bottom surface of the dish in any culture. After that, it was confirmed under a microscope that these adherent cells were grown to near confluence, and 19 days later, adherent cells of all dishes were detached from the dishes by trypsin treatment and adhered using trypan blue solution. The cells were counted. This was used as a bone marrow mesenchymal stem cell in the next culture.
2. Induction of differentiation into chondrocytes 1. The bone marrow mesenchymal stem cells that had been cultured and collected in the above manner were induced to differentiate into chondrocytes by the following method. The culture medium was prepared by adding TGF-β3 (10 ng/ml) which is a differentiation inducing factor and insulin-like growth factor (IGF, 100 ng/ml) to a DMEM medium as a differentiation inducing medium, which was used. .. In addition, a DMEM medium containing neither TGF-β3 nor IGF was prepared as a control medium, and culturing was performed using this medium.
[1] Bone marrow mesenchymal stem cells were seeded in a 100Φ culture dish at a cell density of 1×10 3 cells/cm 2, and cultured for 10 days according to a standard method.
[2] During the culture of the above [1], the bone marrow mesenchymal stem cells adhered to the bottom surface of the 100Φ culture dish with time were detached by trypsin treatment and collected using a centrifuge.
[3] Next, using the collected bone marrow mesenchymal stem cells as a sample, the expression level of mRNA of aggrecan, which is a protein specific to chondrocytes, was expressed by a real-time RT-PCR method (real-time reverse transcription polymerase chain reaction method). %) to confirm that the bone marrow mesenchymal stem cells were differentiated into chondrocytes. At this time, the expression level of primary human chondrocytes was set as 100% and used as an index.
[4] During the confirmation of the mRNA expression level in [3], the morphological changes of cells in the 100Φ culture dish were also observed with an inverted microscope over time.
[5] This observation result is as illustrated in FIGS. 2 and 3. FIG. 2 is a view showing the observation results in the culture inducing differentiation of bone marrow mesenchymal stem cells into chondrocytes, where (A) is the first day of culture, (B) the second day of culture, and (C) the fourth day of culture. It's an eye. FIG. 3 is a view showing the observation results in the control culture, (A) shows the first day of culture, (B) the second day of culture, and (C) the fourth day of culture.
[6] In the differentiation-inducing culture shown in FIG. 2, cells are formed into a polygonal shape from the elongated shape as shown in FIG. 2(A) to the polygonal shape each time the culture days are followed as shown in FIGS. 2(B) and 2(C). It was confirmed that the morphology was changed. On the other hand, in the control culture shown in FIG. 3, it was confirmed that the cells remained elongated and had almost no change in the number of culture days shown in FIGS. 3(A)(B)(C). ..
[7] Next, based on the observation data by the microscope image obtained in the above [6], the projected area value (cell area value) and major axis value of 50 cells on the adhesive surface are calculated using a computer, Calculated from the obtained cell area value and major axis value, the following equation (1)
From this, the ratio of the area of the major axis to the area of the minor axis (that is, corresponding to the degree of morphological change of cells or tissues) was calculated.
3. Diagnosis of the degree of differentiation of cells based on the degree of morphological change of cells, and 2. The aggrecan mRNA expression level (aggrecan expression rate (%)) confirmed in [3] of the above, and the above 2. The major axis/minor axis area ratio (morphological change degree) calculated in [7] above was compared to examine the correlation between the two. Then, as a result, Table 1 exemplifies the ratio of cells in which the aggrecan mRNA expression level (aggrecan expression rate (%)) and the major axis/minor axis area ratio are 0.3 or more.
Of course, the present invention is not limited to the above examples, and it goes without saying that various details can be made in the details.
Claims (15)
から、長径短径面積比を算出し、この長径短径面積比から細胞の分化度を診断することを特徴とする細胞の分化度自動診断方法。The method for automatically diagnosing the degree of differentiation of cells according to claim 2, wherein the following formula (1) is used based on observation data having both an area value and a major axis value.
A method for automatically diagnosing the differentiation degree of cells, which comprises calculating the major axis/minor axis area ratio from the above and diagnosing the cell differentiation degree from the major axis/minor axis area ratio.
から長径短径面積比を算出し、この長径短径面積比から細胞の形態変化度を数値化するものであることを特徴とする請求項１２の細胞の分化度自動診断装置。The observation data processing means uses the following equation (1) based on the observation data.
13. The automatic cell differentiation degree diagnostic device according to claim 12, wherein the major axis/minor axis area ratio is calculated from the above, and the morphological change degree of the cell is quantified from this major axis/minor axis area ratio.
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