Name: 著者スポットライト:イメージングフローサイトメトリーを使用した微生物オートアグリゲーションの研究の進展
Uploaded: 2023-09-29T14:00:00
Description: Read this Scientific Article Protocol about Author Spotlight: Advancing Research in Microbial Auto Aggregation Using Imaging Flow Cytometry at JoVE.com

この研究は、イスラエル科学財団(Grant 119/16)とIKGへのIMoh助成金(3-15656)の支援を受けました。R.S.はクライトマン・フェローシップの支援を受けています。

.ast ファイルは、 例として Lacticaseibacillus rhamnosus GG (LGG) のテンプレートを含み、 Supplementary Coding File 1 で提供されています。
1. 培地の準備
<ol><li>製造元の指示に従って乳酸桿菌MRSブロス(1 Lの脱イオン水に55 g)と1.5%(w / v)寒天を含む乳酸桿菌MRS寒天プレートを準備します( 材料の表を参照)。オートクレーブ滅菌後、培地は直接?...

イメージングフローサイトメトリーを用いた微生物オートアグリゲーションの定量解析

<ol>
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Tol 5 mediating high adhesiveness to various abiotic surfaces.</a> PLoS One. 7, e48830 (2012).</li><li>Inoue, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+characterization+of+low-molecular-weight+component+protein,+Flp,+in+Actinobacillus+actinomycetemcomitans+fimbriae.">Molecular characterization of low-molecular-weight component protein, Flp, in Actinobacillus actinomycetemcomitans fimbriae.</a> Medical Microbiology and Immunology. 42 (4), 253-258 (1998).</li><li>Boddey, J. A., Flegg, C. P., Day, C. J., Beacham, I. R., Peak, I. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temperature-regulated+microcolony+formation+by+Burkholderia+pseudomallei+requires+pilA+and+enhances+association+with+cultured+human+cells.">Temperature-regulated microcolony formation by Burkholderia pseudomallei requires pilA and enhances association with cultured human cells.</a> Infection and Immunity. 74 (9), 5374-5381 (2006).</li><li>Suissa, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Context-dependent+differences+in+the+functional+responses+of+Lactobacillaceae+strains+to+fermentable+sugars.">Context-dependent differences in the functional responses of Lactobacillaceae strains to fermentable sugars.</a> Frontiers in Microbiology. 13, 949932 (2022).</li><li>Isenring, J., Geirnaert, A., Lacroix, C., Stevens, M. J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bistable+auto-aggregation+phenotype+in+Lactiplantibacillus+plantarum+emerges+after+cultivation+in+in+vitro+colonic+microbiota.">Bistable auto-aggregation phenotype in Lactiplantibacillus plantarum emerges after cultivation in in vitro colonic microbiota.</a> BMC Microbiology. 21, 268 (2021).</li><li>Kos, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Adhesion+and+aggregation+ability+of+probiotic+strain+Lactobacillus+acidophilus+M92.">Adhesion and aggregation ability of probiotic strain Lactobacillus acidophilus M92.</a> Journal of Applied Microbiology. 94 (6), 981-987 (2003).</li><li>Zommiti, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+assessment+of+the+probiotic+properties+and+bacteriocinogenic+potential+of+Pediococcus+pentosaceus+MZF16+isolated+from+artisanal+tunisian+meat+&amp;#34;Dried+Ossban&amp;#34;.">In vitro assessment of the probiotic properties and bacteriocinogenic potential of Pediococcus pentosaceus MZF16 isolated from artisanal tunisian meat &amp;#34;Dried Ossban&amp;#34;.</a> Frontiers in Microbiology. 9, 2607 (2018).</li><li>Suissa, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolic+rewiring+of+the+probiotic+bacterium+rhamnosus&lt;/em&gt;+GG+contributes+to+cell-wall+remodeling+and+antimicrobials+production.">Metabolic rewiring of the probiotic bacterium rhamnosus&lt;/em&gt; GG contributes to cell-wall remodeling and antimicrobials production.</a> bioRxiv. , (2023).</li><li>Connell, J. L., Kim, J., Shear, J. B., Bard, A. J., Whiteley, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+monitoring+of+quorum+sensing+in+3D-printed+bacterial+aggregates+using+scanning+electrochemical+microscopy.">Real-time monitoring of quorum sensing in 3D-printed bacterial aggregates using scanning electrochemical microscopy.</a> Proceedings of the National Academy of Sciences of the United States of America. 111 (51), 18255-18260 (2014).</li><li>Misawa, N., Blaser, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+and+characterization+of+autoagglutination+activity+by+Campylobacter+jejuni.">Detection and characterization of autoagglutination activity by Campylobacter jejuni.</a> Infection and Immunity. 68 (11), 6168-6175 (2000).</li><li>Sherlock, O., Schembri, M. A., Reisner, A., Klemm, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Novel+roles+for+the+AIDA+adhesin+from+diarrheagenic+Escherichia+coli:+cell+aggregation+and+biofilm+formation.">Novel roles for the AIDA adhesin from diarrheagenic Escherichia coli: cell aggregation and biofilm formation.</a> Journal of Bacteriology. 186 (23), 8058-8065 (2004).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+flow+cytometry.">Imaging flow cytometry.</a> Nature Reviews Methods Primers. 2, 87 (2022).</li><li>Wang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metabolism+characteristics+of+lactic+acid+bacteria+and+the+expanding+applications+in+food+industry.">Metabolism characteristics of lactic acid bacteria and the expanding applications in food industry.</a> Frontiers in Bioengineering and Biotechnology. 9, 612285 (2021).</li><li>Turroni, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+dialogue+between+the+human+gut+microbiota+and+the+host:+a+Lactobacillus+and+Bifidobacterium+perspective.">Molecular dialogue between the human gut microbiota and the host: a Lactobacillus and Bifidobacterium perspective.</a> Cellular and Molecular Life Sciences. 71, 183-203 (2014).</li><li>Zuba-Surma, E. K., Kucia, M., Abdel-Latif, A., Lillard, J. W., Ratajczak, M. Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ImageStream+System:+a+key+step+to+a+new+era+in+imaging.">The ImageStream System: a key step to a new era in imaging.</a> Folia Histochemica et Cytobiologica. 45, 279-290 (2007).</li><li>Dashkova, V., Malashenkov, D., Poulton, N., Vorobjev, I., Barteneva, N. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+flow+cytometry+for+phytoplankton+analysis.">Imaging flow cytometry for phytoplankton analysis.</a> Methods. 112, 188-200 (2017).</li><li>Maan, H., Gilhar, O., Porat, Z., Kolodkin-Gal, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacillus+subtilis+colonization+of+arabidopsis+thaliana+roots+induces+multiple+biosynthetic+clusters+for+antibiotic+production.">Bacillus subtilis colonization of arabidopsis thaliana roots induces multiple biosynthetic clusters for antibiotic production.</a> Frontiers in Cellular and Infection Microbiology. 11, 722778 (2021).</li><li>Maan, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+flow+cytometry+reveals+a+dual+role+for+exopolysaccharides+in+biofilms:+To+promote+self-adhesion+while+repelling+non-self-community+members.">Imaging flow cytometry reveals a dual role for exopolysaccharides in biofilms: To promote self-adhesion while repelling non-self-community members.</a> Computational and Structural Biotechnology Journal. 20, 15-25 (2022).</li><li>Konieczny, M., Rhein, P., Czaczyk, K., Bialas, W., Juzwa, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+flow+cytometry+to+study+biofilm-associated+microbial+aggregates.">Imaging flow cytometry to study biofilm-associated microbial aggregates.</a> Molecules. 26 (23), 7096 (2021).</li><li>Niederdorfer, R., Peter, H., Battin, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Attached+biofilms+and+suspended+aggregates+are+distinct+microbial+lifestyles+emanating+from+differing+hydraulics.">Attached biofilms and suspended aggregates are distinct microbial lifestyles emanating from differing hydraulics.</a> Nature Microbiology. 1, 16178 (2016).</li></ol>

フローサイトメトリーは、真核細胞の蛍光強度を定量化するために広く使用されている方法ですが、細菌細胞のサイズが大きいか凝集体が小さいため、細菌細胞の正確な測定が得られない場合があります。これらの要因は、さまざまな条件での自己凝集の正確な定量化と凝集体形成の基礎レベルに大きな影響を与える可能性があります。これに対処するために、イメージングフローサイトメ?...

細菌の自己凝集は、バイオフィルム形成の主要なステップと考えられています。このプロセス(自己凝集または凝集とも呼ばれる)では、同じ種類の細菌が多細胞塊を形成し、最終的に培養チューブの底に沈殿するか、標的組織または表面に付着します1。
自己凝集は広く観察された現象であり、これまでに日和見病原体Acinetobacter baumannii2、歯科病原体Aggregobacter actinomycetemcomitans3、新興病原体Burkholderia pseudomallei4などのグラム陰性病原体で示されています。自己凝集は、いくつかのプロバイオティクスグラム陽性株5,6,7,8でも記載されています。Lactobacillus (L.) acidophilusでは、自己凝集は部分的にS層タンパク質によって媒介され、キシラン7への接着と相関していました。同様に、プロバイオティクス種であるLacticaseibacillus rhamnosus GG、Lacticaseibacillus casei、L. acidophilus、Lacticaseibacillus paracasei、およびLactiplantibacillus plantarumのグルコース依存性自己凝集と接着特性(ムチンへの接着によって判断)の誘導との間に相関関係があることを発見しました5.自己凝集の増加は、グルコースとその異化産物に応答した細胞性アドヘシンの発現の変化を反映している可能性が最も高い9。自己凝集の分子メカニズムはまだ決定されていませんが、このプロセスが凝集した細菌の表現型を変化させ、環境ストレス因子1に対する耐性を高め、クォーラムセンシング分子10に対する感受性を高めることが示されています。
自己集約の測定には、いくつかのアプローチが使用されてきました。1つの実験的アプローチは、培養物を狭い培養チューブに一定時間静的に放置することです。対照培養物は濁ったままですが、自己凝集培養物はチューブの底に沈殿します。より定量的なアプローチは、沈降または沈降アッセイ11による自己凝集を測定する。
フローサイトメトリーは、近年、細菌の自己凝集を調べるためにますます採用されています。この方法は、サイズが約0.5〜1000μmの粒子を分析するのに適しています。単一の細菌または形成された凝集体は、流体中に懸濁され、流れに供給され、1つずつ検出することができる11。前方散乱光を記録することで、細胞または凝集体の相対的なサイズを測定できます。これは比較的高速で簡単ですが、集計サイズや集計内の平均セル数など、いくつかのパラメーターを検出できません。したがって、このアプローチは顕微鏡的に補完することができ、より多くのパラメータをチェックすることができます12。しかし、従来の顕微鏡検査は時間がかかるため、試験するサンプルの数や分析の統計的検出力が制限されていました。一般に、イメージングフローサイトメトリーは、細胞形態および表現型の同時解析、画像ベースの解析の実施、まれな事象の検出、およびフローサイトメトリーデータの検証など、従来のフローサイトメトリーと比較していくつかの特徴を提供する13。これらの利点により、フローサイトメトリーの機能が向上し、細胞集団のより詳細な検査が容易になります。
この研究は、乳酸菌(LAB)の自己凝集をモニターするためのイメージングフローサイトメトリーのための貴重なプロトコルを提供します。これらのグラム陽性桿体は通性嫌気性菌であり、LABグループに属しています。これらの効率的なグルコース発酵槽は、炭水化物代謝14の主な最終産物として乳酸を生成します。これらの細菌は、マイクロバイオームの有益なコアメンバーであり、ヒトや動物の消化管(GIT)だけでなく、女性の泌尿生殖管にも自然に見られます15。したがって、それらの自己凝集特性の正確な特性評価は、バイオテクノロジーおよび臨床で高い関心を集めています。
これまでの知見では、自己凝集の基礎レベルはプロバイオティクス株によって異なることが示されました。この不均一性は、炭素源として使用されるさまざまな炭水化物の影響を受けます5。プロバイオティクス細菌のこの基本的な特性を克服するために、食事からの炭水化物の影響をIFCを使用して単一細胞レベルでの自己凝集にモニターしました。このIFCベースのアプローチは、従来のフローサイトメーターのパワーと速度を顕微鏡の分解能と組み合わせたものです。したがって、表現型的に定義された方法で高速の複雑な形態測定が可能になります16,17。このアプローチは、他のプロバイオティクス細菌や病原性細菌にも適用でき、蛍光レポーターと組み合わせて遺伝子発現をモニターしたり、蛍光標識株と組み合わせて不均一な凝集体中の特定の細菌種の存在と存在量をモニターしたりできます。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>14 mL culture tubes</td>
			<td>Falcon</td>
			<td>352051</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL centrifuge tube</td>
			<td>Falcon</td>
			<td>352096</td>
			<td></td>
		</tr>
		<tr>
			<td>Bacto Agar</td>
			<td>Baeton,Dickinson and Company</td>
			<td>214010</td>
			<td></td>
		</tr>
		<tr>
			<td>Bacto Typtic Soy Broth</td>
			<td>Baeton,Dickinson and Company</td>
			<td>211825</td>
			<td></td>
		</tr>
		<tr>
			<td>D-(+)-Glucose</td>
			<td>Sigma</td>
			<td>G7021-1KG</td>
			<td></td>
		</tr>
		<tr>
			<td>D-(+)-Raffinose pentahydrate</td>
			<td>Sigma</td>
			<td>83400-25G</td>
			<td></td>
		</tr>
		<tr>
			<td>Difco Lactobacilli MRS broth</td>
			<td>Baeton,Dickinson and Company</td>
			<td>288130</td>
			<td></td>
		</tr>
		<tr>
			<td>EASY-LOCK MICROPR. 1.5 mL (Eppendorf)</td>
			<td>FL medical</td>
			<td>23053</td>
			<td></td>
		</tr>
		<tr>
			<td>IDEAS Software</td>
			<td>Amnis/EMD Millipore</td>
			<td>N/A</td>
			<td>&#160;Details available at: https://www.merckmillipore.com/INTL/en/20150212_144049?ReferrerURL=https%3A%2F%2Fwww.google.com%2F&#38;bd=1</td>
		</tr>
		<tr>
			<td>ImageStream X Mark II</td>
			<td>Amnis/EMD Millipore</td>
			<td>N/A</td>
			<td>&#160;Details available at: https://www.merckmillipore.com/INTL/en/20150121_205948?ReferrerURL=https%3A%2F%2Fwww.google.com%2F</td>
		</tr>
		<tr>
			<td>MOPS, 3-(N-morpholino)propanesulfonic acid</td>
			<td>Fisher bioreagents</td>
			<td>BP308-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Potassium phosphate dibasic</td>
			<td>Fisher Scientific, 174.18 g/mol</td>
			<td>BP363-1</td>
			<td></td>
		</tr>
		<tr>
			<td>Potassium phosphate monobasic</td>
			<td>Sigma, 136.09 g/mol</td>
			<td>P0662-500G</td>
			<td></td>
		</tr>
	</tbody>
</table>

imaging flow cytometry to study microbial autoaggregation

有益なプロバイオティクス細菌は、宿主で重要な役割を果たし、感染症に対する免疫を含むさまざまな健康上の利点を提供します。ラクトバチル科は、プロバイオティクスの特性が確認されたグラム陽性菌で構成されています。この研究では、ラクトバチル科の種をモデルとして利用し、細胞凝集の研究におけるシングルセルハイスループット分析の有効性を実証します。焦点は、食事からの単純な炭水化物に対するこれらの有益な種の反応を分析することです。
この研究は、イメージングフローサイトメトリー(IFC)が、炭水化物の存在下と非存在下でのプロバイオティクス細菌の集合における基本的な違いをどのように克服できるかを示しています。IFCは、従来のフローサイトメトリーのパワーとスピードを顕微鏡法の空間分解能と組み合わせることで、有益な細菌株と病態のライブラリー全体で表現型的に定義された方法で、複雑な形態測定を高速に行うことができます。このプロトコルは、ラクトバクラ科の種の自己凝集に関する洞察を提供し、食事性炭水化物に対するそれらの応答に光を当て、これらのプロバイオティクス細菌の有益な効果の背後にあるメカニズムの理解に貢献します。

Bacterial autoaggregation is considered a primary step in biofilm formation. In this process (sometimes also called autoagglutination or flocculation), bacteria of the same type form multicellular clumps that eventually settle at the bottom of culture tubes or attach to their target tissue or surface1.
Autoaggregation is a widely observed phenomenon and has been shown so far in Gram-negative pathogens such as the opportunistic pathogen Acinetobacter baumannii2, the dental pathogen Aggregobacter actinomycetemcomitans3, and the emerging pathogen Burkholderia pseudomallei4. Autoaggregation has also been described in several probiotic Gram-positive strains5,6,7,8. In Lactobacillus (L.) acidophilus, autoaggregation was partially mediated by S-layer proteins and correlated with an adhesion to xylan7. Similarly, we found a correlation between glucose-dependent autoaggregation and induction of the adhesive properties (as judged by adhesion to mucin) of the probiotic species Lacticaseibacillus rhamnosus GG, Lacticaseibacillus casei, L. acidophilus, Lacticaseibacillus paracasei, and Lactiplantibacillus plantarum5. The increased autoaggregation most likely reflected changes in the expression of cellular adhesins in response to glucose and its catabolites9. While the molecular mechanisms of autoaggregation remain to be determined, it has been shown that this process alters the phenotype of the aggregated bacteria and grants them enhanced tolerance to environmental stressors1, as well as increased sensitivity to quorum sensing molecules10.
Several approaches have been used to measure autoaggregation; one experimental approach is to let cultures stand statically in narrow culture tubes for a given time. Control cultures remain turbid, whereas autoaggregation cultures will settle at the bottom of the tube. A more quantitative approach measures autoaggregation by sedimentation or settling assay11.
Flow cytometry has also been increasingly employed in recent years to investigate bacterial autoaggregation. This method is appropriate for analyzing particles between approximately 0.5 and 1000 &#181;m in size. The single bacterium or formed aggregates are suspended in fluid, fed into a stream, and can be detected one by one11. Recording forward scattered light allows measuring the relative size of the cell or aggregate. It is relatively fast and straightforward but cannot detect several parameters, such as aggregate size or the average number of cells in aggregates. Therefore, this approach can be complemented microscopically, allowing more parameters to be checked12. However, traditional microscopy is time-consuming and thereby limits the number of tested samples and the statistical power of the analysis. In general, imaging flow cytometry provides several features compared to traditional flow cytometry, such as simultaneous analysis of cell morphology and phenotype, conducting image-based analysis, detecting rare events, and validating flow cytometry data13. These advantages enhance the capabilities of flow cytometry and facilitate a more detailed examination of cell populations.
This study provides a valuable protocol for imaging flow cytometry to monitor autoaggregation in lactic acid bacteria (LAB). These Gram-positive rods are facultative anaerobes and belong to the LAB group. These efficient glucose fermenters generate lactic acid as their main end-product of carbohydrate metabolism14. These bacteria are beneficial core members of the microbiome and are naturally found in the gastrointestinal tract (GIT) of humans and animals, as well as in the urogenital tract of females15. Therefore, the exact characterization of their autoaggregation properties is of high biotechnological and clinical interest.
Our previous findings indicated that the basal level of autoaggregation differs between different probiotic strains. This heterogeneity is affected by the different carbohydrates used as a carbon source5. To overcome this fundamental property of probiotic bacteria, the effects of carbohydrates from the diet were monitored on autoaggregation on the single-cell level using IFC. This IFC-based approach combines the power and speed of traditional flow cytometers with the microscope&#39;s resolution. Therefore, it allows high-rate complex morphometric measurements in a phenotypically defined way16,17. This approach can be extended to other probiotic and pathogenic bacteria, combined with fluorescent reporters to monitor gene expression, and fluorescently labeled strains to monitor the presence and abundance of specific bacterial species in heterogeneous aggregates.

著者スポットライト:イメージングフローサイトメトリーを使用した微生物オートアグリゲーションの研究の進展

微生物の自己凝集を研究するためのイメージングフローサイトメトリー

This study utilized Lactobacillus species as a model to demonstrate the effectiveness of imaging flow cytometry analysis in studying microbial autoaggregation. The focus is on analyzing the response of autoaggregation of Lactobacillus species to simple carbohydrates from the diet. The most used methods for measuring autoaggregation are spectral photometry, which measures microbial suspensions, turbidity, or optical density, and traditional microscopy techniques, such as bright field, phase contrast, and fluorescent microscopy.When talking about hight-throughput imaging, one major experimental challenge is single event segmentation. In this protocol, it is a single aggregate. Imaging flow cytometry addresses this challenge elegantly and give researchers a powerful tool for studying autoaggregation.

この結果は、この方法がLAB細菌の食事糖に対する自己凝集の違いを容易に測定できることを示しています。個体を凝集体から分離することにより、この方法は、食餌からの発酵性または非発酵性の糖に応答して、すべてのイベントのうち、凝集イベントの人口の割合を計算することを可能にする。さらに、治療間で凝集体の母集団の平均サイズに違いがあるかどうかを測定することができま?...

Read this Scientific Article Protocol about Author Spotlight: Advancing Research in Microbial Auto Aggregation Using Imaging Flow Cytometry at JoVE.com

このプロトコルは、イメージングフローサイトメトリーを使用して微生物の自己凝集を測定するための定量的アプローチを説明しています。

Beneficial and probiotic bacteria play essential roles in their hosts, providing various health benefits, including immunity to infectious diseases. The ...

この研究では、ラクトバチルス菌種をモデルとして利用し、微生物の自己凝集研究におけるイメージングフローサイトメトリー分析の有効性を実証しました。焦点は、食事からの単純な炭水化物に対するラクトバチルス種の自己凝集の応答を分析することです。オートアグリゲーションの測定に最も使用されている方法は、微生物懸濁液、濁度、または光学密度を測定するスペクトル測光法と、明視野、位相コントラスト、蛍光顕微鏡などの従来の顕微鏡技術です。ハイスループットイメージングについて語るとき、実験上の大きな課題の1つはシングルイベントのセグメンテーションです。このプロトコルでは、1 つのアグリゲートです。イメージングフローサイトメトリーは、この課題にエレガントに対処し、研究者に自己凝集を研究するための強力なツールを提供します。

imaging-flow-cytometry-to-study-microbial-autoaggregation

Research

JoVE Journal

Biology

Imaging Flow Cytometry to Study Microbial Autoaggregation

Beneficial and probiotic bacteria play essential roles in their hosts, providing various health benefits, including immunity to infectious diseases. The Lactobacillaceae family consists of Gram-positive bacteria with confirmed probiotic properties. This study utilizes Lactobacillaceae species as a model to demonstrate the effectiveness of single-cell high throughput analysis in studying cellular aggregation. The focus is on analyzing the response of these beneficial species to simple carbohydrates from the diet.
The study showcases how Imaging Flow Cytometry (IFC) can overcome the fundamental differences in the assembly of probiotic bacteria in the presence and absence of carbohydrates. IFC combines the power and speed of conventional flow cytometry with the spatial resolution of microscopy, enabling high-rate complex morphometric measurements in a phenotypically defined manner across a library of beneficial bacterial strains and conditions. This protocol provides insights into the autoaggregation of Lactobacillaceae species and sheds light on their response to dietary carbohydrates, contributing to understanding the mechanisms behind the beneficial effects of these probiotic bacteria.

This protocol describes a quantitative approach to measure microbial autoaggregation using imaging flow cytometry.

生物学

Lactobacillaceae Sample Preparation for Flow Cytometric Analysis

Start by inoculating five milliliters of lactobacilli MRS broth with a single colony of the lactobacilli strain, incubated at 37 degrees Celsius under static conditions overnight. Dilute the cell culture in a one-to-100 ratio in three milliliters of 50%supplemented tryptic soy broth, vortex the culture, and incubate it. Then invert the tube to mix the cells in the medium before transferring 200 to 300 microliters of the sample into a 1.5 milliliter micro centrifuge tube.

ラクトバチル科 フローサイトメトリー解析のためのサンプル調製

Flow Cytometric Data Acquisition of Microbial Aggregates

To begin the flow cytometric analysis, first set the 785-nanometer laser to a power of five milliwatts for dark field measurements. Use a 60X lens with a numerical aperture of 0.9. Then select the high-sensitivity setting and set the speed to low.To ensure calibration bead stability, press the Play button in the fluidics box and examine the bead images, which should appear sharp and clear. Generate a new scatterplot in the workspace box by selecting New Scatterplot. Then select the area in the Brightfield channel that corresponds to the SSC channel intensity and exclude the calibration beads that are running concurrently within the sample.Next, press the Load button and position a tube containing the Lactobacilli sample in the holder. In the Acquisition Settings box, enter the sample name and specify the location for data storage. Set the number of events to be collected, typically within the range of 10, 000 to 20, 000 events.Now, begin the acquisition process by clicking the Record button located in the Acquisition box. The process will halt after reaching the specified volume of events. Press the Return button to unload the tube and remove it from the holder as prompted in the popup window.After repeating the process for all samples, save the template to maintain data acquisition uniformity. For data analysis, to load the raw file into the analysis software, click on File and open the rif file. In the opened window, select Use Acquisition Analysis and then click OK.Next, to create a histogram of the gradient root mean square, click the New Histogram button and choose the population from the acquisition to analyze.Under the X Axis feature, select Gradient RMS of the Brightfield channel. Next, place a gate to exclude non-focused events by clicking the Create Line Region button in the analysis area. Create a scatterplot of the area versus the aspect ratio by clicking the New Scatterplot button in the analysis area.Select the focused population in the New Scatterplot window. Then select the area of the Brightfield channel for the X-Axis feature. Choose the aspect ratio for the Y-Axis feature.Draw a gate on the scatterplot using the Create Rectangle button based on the area value for the aggregate events population. Similarly, draw another gate for the singles and small aggregates population. Save your data analysis as a template by clicking the File tab, choosing Save As Template ast, and then open the next sample file under the same template to create the data analysis file.To measure the aggregate size distribution, start by plotting a histogram of the area of the aggregation events population. Save the data analysis by clicking on the file and selecting the Save As Template option. After saving, open the next sample file under the same template for the data analysis file.Single cells, small aggregates, large aggregates, and chains were observed in LGG and L.paracasei but it was not possible to distinguish between chains and larger aggregates. Significant variations in the aggregation characteristics of different LAB strains were observed in response to fermentable or non-fermentable sugars.