SPIRE: a Searchable, Planetary-scale mIcrobiome REsource.

Meta'omic data on microbial diversity and function accrue exponentially in public repositories, but derived information is often siloed according to data type, study or sampled microbial environment. Here we present SPIRE, a Searchable Planetary-scale mIcrobiome REsource that integrates various consistently processed metagenome-derived microbial data modalities across habitats, geography and phylogeny. SPIRE encompasses 99 146 metagenomic samples from 739 studies covering a wide array of microbial environments and augmented with manually-curated contextual data. Across a total metagenomic assembly of 16 Tbp, SPIRE comprises 35 billion predicted protein sequences and 1.16 million newly constructed metagenome-assembled genomes (MAGs) of medium or high quality. Beyond mapping to the high-quality genome reference provided by proGenomes3 (http://progenomes.embl.de), these novel MAGs form 92 134 novel species-level clusters, the majority of which are unclassified at species level using current tools. SPIRE enables taxonomic profiling of these species clusters via an updated, custom mOTUs database (https://motu-tool.org/) and includes several layers of functional annotation, as well as crosslinks to several (micro-)biological databases. The resource is accessible, searchable and browsable via http://spire.embl.de.

Drivers and determinants of strain dynamics following fecal microbiota transplantation.

Fecal microbiota transplantation (FMT) is a therapeutic intervention for inflammatory diseases of the gastrointestinal tract, but its clinical mode of action and subsequent microbiome dynamics remain poorly understood. Here we analyzed metagenomes from 316 FMTs, sampled pre and post intervention, for the treatment of ten different disease indications. We quantified strain-level dynamics of 1,089 microbial species, complemented by 47,548 newly constructed metagenome-assembled genomes. Donor strain colonization and recipient strain resilience were mostly independent of clinical outcomes, but accurately predictable using LASSO-regularized regression models that accounted for host, microbiome and procedural variables. Recipient factors and donor-recipient complementarity, encompassing entire microbial communities to individual strains, were the main determinants of strain population dynamics, providing insights into the underlying processes that shape the post-FMT gut microbiome. Applying an ecology-based framework to our findings indicated parameters that may inform the development of more effective, targeted microbiome therapies in the future, and suggested how patient stratification can be used to enhance donor microbiota colonization or the displacement of recipient microbes in clinical practice.

Dysbiosis of the Female Murine Gut Microbiome Exacerbates Neutrophil-mediated Vascular Allograft Injury by Affecting Immunoregulation by Acetate.

BACKGROUND: The gut microbiota affects immune responses that cause organ transplant rejection, but the mechanisms by which this occurs remain poorly understood. METHODS: We have examined, in a murine model, how disruption of the gut microbiota with antibiotics early in life alters this microbial community later in life to affect immune responses that injure vascular allografts. RESULTS: Analysis of 16S rRNA and whole genome sequencing of the gut microbiota demonstrated that early life disruption of this microbial community with antibiotics caused a reduction in taxa and enzymatic genes involved in the synthesis of acetate, an immunoregulatory metabolite in mice and humans. When allograft vascular injury was examined, early life disruption of the gut microbiota increased neutrophil accumulation and related medial injury of transplanted arteries. Normalizing the gut microbiota by co-housing and oral administration of acetate prevented neutrophil-mediated vascular allograft injury. CONCLUSIONS: Dysbiosis of the gut microbiome that reduces its production of the immunoregulatory metabolite acetate exacerbates neutrophil-mediated allograft vascular injury.

A faecal microbiota signature with high specificity for pancreatic cancer.

BACKGROUND: Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression. OBJECTIVE: To explore the faecal and salivary microbiota as potential diagnostic biomarkers. METHODS: We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase. RESULTS: Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation. CONCLUSION: Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Meconium Microbiome of Very Preterm Infants across Germany.

Meconium constitutes infants' first bowel movements postnatally. The consistency and microbial load of meconium are different from infant and adult stool. While recent evidence suggests that meconium is sterile in utero, rapid colonization occurs after birth. The meconium microbiome has been associated with negative health outcomes, but its composition is not well described, especially in preterm infants. Here, we characterized the meconium microbiomes from 330 very preterm infants (gestational ages 28 to 32 weeks) from 15 hospitals in Germany and in fecal samples from a subset of their mothers (N = 217). Microbiome profiles were compiled using 16S rRNA gene sequencing with negative and positive controls. The meconium microbiome was dominated by Bifidobacterium, Staphylococcus, and Enterococcus spp. and was associated with gestational age at birth and age at sample collection. Bifidobacterial abundance was negatively correlated with potentially pathogenic genera. The amount of bacterial DNA in meconium samples varied greatly across samples and was associated with the time since birth but not with gestational age or hospital site. In samples with low bacterial load, human mitochondrial sequences were highly amplified using commonly used, bacterial-targeted 16S rRNA primers. Only half of the meconium samples contained sufficient bacterial material to study the microbiome using a standard approach. To facilitate future meconium studies, we present a five-level scoring system ("MecBac") that predicts the success of 16S rRNA bacterial sequencing for meconium samples. These findings provide a foundational characterization of an understudied portion of the human microbiome and will aid the design of future meconium microbiome studies. IMPORTANCE Meconium is present in the intestines of infants before and after birth and constitutes their first bowel movements postnatally. The consistency, composition and microbial load of meconium is largely different from infant and adult stool. While recent evidence suggests that meconium is sterile in utero, rapid colonization occurs after birth. The meconium microbiome has been associated with short-term and long-term negative health outcomes, but its composition is not yet well described, especially in preterm infants. We provide a characterization of the microbiome structure and composition of infant meconium and maternal feces from a large study cohort and propose a method to evaluate meconium samples for bacterial sequencing suitability. These findings provide a foundational characterization of an understudied portion of the human microbiome and will aid the design of future meconium microbiome studies.

metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes.

SUMMARY: Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity between species and strains can identify 'subspecies', which are a useful intermediary. High-throughput identification and profiling of subspecies is not yet supported in the microbiome field. Here, we use an operational definition of subspecies based on single nucleotide variant (SNV) patterns within species to identify and profile subspecies in metagenomes, along with their distinctive SNVs and genes. We incorporate this method into metaSNV v2, which extends existing SNV-calling software to support further SNV interpretation for population genetics. These new features support microbiome analyses to link SNV profiles with host phenotype or environment and niche-specificity. We demonstrate subspecies identification in marine and fecal metagenomes. In the latter, we analyze 70 species in 7524 adult and infant subjects, supporting a common subspecies population structure in the human gut microbiome and illustrating some limits in subspecies calling. AVAILABILITY AND IMPLEMENTATION: Source code, documentation, tutorials and test data are available at https://github.com/metasnv-tool/metaSNV and https://metasnv.embl.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Towards the biogeography of prokaryotic genes.

Microbial genes encode the majority of the functional repertoire of life on earth. However, despite increasing efforts in metagenomic sequencing of various habitats1-3, little is known about the distribution of genes across the global biosphere, with implications for human and planetary health. Here we constructed a non-redundant gene catalogue of 303 million species-level genes (clustered at 95% nucleotide identity) from 13,174 publicly available metagenomes across 14 major habitats and use it to show that most genes are specific to a single habitat. The small fraction of genes found in multiple habitats is enriched in antibiotic-resistance genes and markers for mobile genetic elements. By further clustering these species-level genes into 32 million protein families, we observed that a small fraction of these families contain the majority of the genes (0.6% of families account for 50% of the genes). The majority of species-level genes and protein families are rare. Furthermore, species-level genes, and in particular the rare ones, show low rates of positive (adaptive) selection, supporting a model in which most genetic variability observed within each protein family is neutral or nearly neutral.

Diversity within species: interpreting strains in microbiomes.

Studying within-species variation has traditionally been limited to culturable bacterial isolates and low-resolution microbial community fingerprinting. Metagenomic sequencing and technical advances have enabled culture-free, high-resolution strain and subspecies analyses at high throughput and in complex environments. This holds great scientific promise but has also led to an overwhelming number of methods and terms to describe infraspecific variation. This Review aims to clarify these advances by focusing on the diversity within bacterial and archaeal species in the context of microbiomics. We cover foundational microevolutionary concepts relevant to population genetics and summarize how within-species variation can be studied and stratified directly within microbial communities with a focus on metagenomics. Finally, we describe how common applications of within-species variation can be achieved using metagenomic data. We aim to guide the selection of appropriate terms and analytical approaches to facilitate researchers in benefiting from the increasing availability of large, high-resolution microbiome genetic sequencing data.

Efficacy of Bifidobacterium longum, B. infantis and Lactobacillus acidophilus probiotics to prevent gut dysbiosis in preterm infants of 28+0-32+6 weeks of gestation: a randomised, placebo-controlled, double-blind, multicentre trial: the PRIMAL Clinical Study protocol.

INTRODUCTION: The healthy 'eubiosis' microbiome in infancy is regarded as the microbiome derived from term, vaginally delivered, antibiotic free, breastfed infants at 4-6 months. Dysbiosis is regarded as a deviation from a healthy state with reduced microbial diversity and deficient capacity to control drug-resistant organisms. Preterm infants are highly sensitive to early gut dysbiosis. Latter has been associated with sepsis and necrotising enterocolitis, but may also contribute to long-term health problems. Probiotics hold promise to reduce the risk for adverse short-term outcomes but the evidence from clinical trials remains inconclusive and none has directly assessed the effects of probiotics on the microbiome at high resolution. METHODS AND ANALYSIS: A randomised, double blind, placebo-controlled study has been designed to assess the safety and efficacy of the probiotic mix of Bifidobacterium longum and infantis and Lactobacillus acidophilus in the prevention of gut dysbiosis in preterm infants between 28+0 and 32+6 weeks of gestation. The study is conducted in 18 German neonatal intensive care units. Between April 2018 and March 2020, 654 preterm infants of 28+0-32+6 weeks of gestation will be randomised in the first 48 hours of life to 28 days of once daily treatment with either probiotics or placebo. The efficacy endpoint is the prevention of gut dysbiosis at day 30 of life. A compound definition of gut dysbosis is used: (1) colonisation with multidrug-resistant organisms or gram-negative bacteria with high epidemic potential or (2) a significant deviation of the gut microbiota composition as compared with healthy term infants. Dysbiosis is determined by (1) conventional microbiological culture and (2) phylogenetic microbiome analysis by high-throughput 16S rRNA and metagenome sequencing. Persistence of dysbiosis will be assessed at 12-month follow-up visits. Side effects and adverse events related to the intervention will be recorded. Key secondary endpoint(s) are putative consequences of dysbiosis. A subgroup of infants will be thoroughly phenotyped for immune parameters using chipcytometry. ETHICS AND DISSEMINATION: Ethics approval was obtained in all participating sites. Results of the trial will be published in peer-review journals, at scientific meetings, on the website (www.primal-study.de) and via social media of parent organisations. TRIAL REGISTRATION NUMBER: DRKS00013197; Pre-results.

The Composition of Midgut Bacteria in Aedes aegypti (Diptera: Culicidae) That Are Naturally Susceptible or Refractory to Dengue Viruses.

The composition, abundance, and diversity of midgut bacteria in mosquitoes can influence pathogen transmission. We used 16S rRNA microbiome profiling to survey midgut microbial diversity in pooled samples of laboratory colonized dengue-refractory, Cali-MIB, and dengue-susceptible, Cali-S Aedes aegypti (Linnaeus). The 16S rRNA sequences from the sugar-fed midguts of adult females clustered to 63 amplicon sequence variants (ASVs), primarily from Proteobacteria, Firmicutes, Flavobacteria, and Actinobacteria. An average of five ASVs dominated the midguts, and most ASVs were present in both Cali-MIB and Cali-S midguts. No differences in abundance were noted at any phylogenetic level (Phylum, Class, Order, Family, Genus) by analysis of composition of microbiome (w = 0). No community diversity metrics were significantly different between refractory and susceptible mosquitoes. These data suggest that phenotypic differences in the susceptibility to dengue virus between Cali-MIB and Cali-S are not likely due to major differences in midgut bacterial communities.

Disruption of the Gut Microbiota With Antibiotics Exacerbates Acute Vascular Rejection.

BACKGROUND: The gut microbiota influences many immunological processes but how its disruption affects transplant rejection is poorly understood. METHODS: Interposition grafting of aortic segments was used to examine vascular rejection. The gut microbiota was disrupted in graft recipients using an antibiotic cocktail (ampicillin, vancomycin, metronidazole, neomycin sulfate) in their drinking water. RESULTS: Treatment of mice with antibiotics severely reduced total bacterial content in the intestine and disrupted the bacterial composition. Short-term treatment of mice for only the first 3 weeks of life resulted in the population of the intestine in mature mice with bacterial communities that were mildly different from untreated mice, containing slightly more Clostridia and less Bacteroides. Antibiotic disruption of the gut microbiota of graft recipients, either for their entire life or only during the first 3 weeks of life, resulted in increased medial injury of allograft arteries that is reflective of acute vascular rejection but did not affect intimal thickening reflective of transplant arteriosclerosis. Exacerbated vascular rejection resulting from disruption of the gut microbiota was related to increased infiltration of allograft arteries by neutrophils. CONCLUSIONS: Disruption of the gut microbiota early in life results in exacerbation of immune responses that cause acute vascular rejection.

A comprehensive method for amplicon-based and metagenomic characterization of viruses, bacteria, and eukaryotes in freshwater samples.

BACKGROUND: Studies of environmental microbiota typically target only specific groups of microorganisms, with most focusing on bacteria through taxonomic classification of 16S rRNA gene sequences. For a more holistic understanding of a microbiome, a strategy to characterize the viral, bacterial, and eukaryotic components is necessary. RESULTS: We developed a method for metagenomic and amplicon-based analysis of freshwater samples involving the concentration and size-based separation of eukaryotic, bacterial, and viral fractions. Next-generation sequencing and culture-independent approaches were used to describe and quantify microbial communities in watersheds with different land use in British Columbia. Deep amplicon sequencing was used to investigate the distribution of certain viruses (g23 and RdRp), bacteria (16S rRNA and cpn60), and eukaryotes (18S rRNA and ITS). Metagenomic sequencing was used to further characterize the gene content of the bacterial and viral fractions at both taxonomic and functional levels. CONCLUSION: This study provides a systematic approach to separate and characterize eukaryotic-, bacterial-, and viral-sized particles. Methodologies described in this research have been applied in temporal and spatial studies to study the impact of land use on watershed microbiomes in British Columbia.

Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb.

Identifying variants causal for complex genetic disorders is challenging. With the advent of whole-exome and whole-genome sequencing, computational tools are needed to explore and analyze the list of variants for further validation. Correlating genetic variants with subject phenotype is crucial for the interpretation of the disease-causing mutations. Often such work is done by teams of researchers who need to share information and coordinate activities. To this end, we have developed a powerful, easy to use Web application, ASPIREdb, which allows researchers to search, organize, analyze, and visualize variants and phenotypes associated with a set of human subjects. Investigators can annotate variants using publicly available reference databases and build powerful queries to identify subjects or variants of interest. Functional information and phenotypic associations of these genes are made accessible as well. Burden analysis and additional reporting tools allow investigation of variant properties and phenotype characteristics. Projects can be shared, allowing researchers to work collaboratively to build queries and annotate the data. We demonstrate ASPIREdb's functionality using publicly available data sets, showing how the software can be used to accomplish goals that might otherwise require specialized bioinformatics expertise. ASPIREdb is available at http://aspiredb.chibi.ubc.ca.

Evaluation of shotgun metagenomics sequence classification methods using in silico and in vitro simulated communities.

BACKGROUND: The field of metagenomics (study of genetic material recovered directly from an environment) has grown rapidly, with many bioinformatics analysis methods being developed. To ensure appropriate use of such methods, robust comparative evaluation of their accuracy and features is needed. For taxonomic classification of sequence reads, such evaluation should include use of clade exclusion, which better evaluates a method's accuracy when identical sequences are not present in any reference database, as is common in metagenomic analysis. To date, relatively small evaluations have been performed, with evaluation approaches like clade exclusion limited to assessment of new methods by the authors of the given method. What is needed is a rigorous, independent comparison between multiple major methods, using the same in silico and in vitro test datasets, with and without approaches like clade exclusion, to better characterize accuracy under different conditions. RESULTS: An overview of the features of 38 bioinformatics methods is provided, evaluating accuracy with a focus on 11 programs that have reference databases that can be modified and therefore most robustly evaluated with clade exclusion. Taxonomic classification of sequence reads was evaluated using both in silico and in vitro mock bacterial communities. Clade exclusion was used at taxonomic levels from species to class-identifying how well methods perform in progressively more difficult scenarios. A wide range of variability was found in the sensitivity, precision, overall accuracy, and computational demand for the programs evaluated. In experiments where distilled water was spiked with only 11 bacterial species, frequently dozens to hundreds of species were falsely predicted by the most popular programs. The different features of each method (forces predictions or not, etc.) are summarized, and additional analysis considerations discussed. CONCLUSIONS: The accuracy of shotgun metagenomics classification methods varies widely. No one program clearly outperformed others in all evaluation scenarios; rather, the results illustrate the strengths of different methods for different purposes. Researchers must appreciate method differences, choosing the program best suited for their particular analysis to avoid very misleading results. Use of standardized datasets for method comparisons is encouraged, as is use of mock microbial community controls suitable for a particular metagenomic analysis.

Year-Long Metagenomic Study of River Microbiomes Across Land Use and Water Quality.

Select bacteria, such as Escherichia coli or coliforms, have been widely used as sentinels of low water quality; however, there are concerns regarding their predictive accuracy for the protection of human and environmental health. To develop improved monitoring systems, a greater understanding of bacterial community structure, function, and variability across time is required in the context of different pollution types, such as agricultural and urban contamination. Here, we present a year-long survey of free-living bacterial DNA collected from seven sites along rivers in three watersheds with varying land use in Southwestern Canada. This is the first study to examine the bacterial metagenome in flowing freshwater (lotic) environments over such a time span, providing an opportunity to describe bacterial community variability as a function of land use and environmental conditions. Characteristics of the metagenomic data, such as sequence composition and average genome size (AGS), vary with sampling site, environmental conditions, and water chemistry. For example, AGS was correlated with hours of daylight in the agricultural watershed and, across the agriculturally and urban-affected sites, k-mer composition clustering corresponded to nutrient concentrations. In addition to indicating a community shift, this change in AGS has implications in terms of the normalization strategies required, and considerations surrounding such strategies in general are discussed. When comparing abundances of gene functional groups between high- and low-quality water samples collected from an agricultural area, the latter had a higher abundance of nutrient metabolism and bacteriophage groups, possibly reflecting an increase in agricultural runoff. This work presents a valuable dataset representing a year of monthly sampling across watersheds and an analysis targeted at establishing a foundational understanding of how bacterial lotic communities vary across time and land use. The results provide important context for future studies, including further analyses of watershed ecosystem health, and the identification and development of biomarkers for improved water quality monitoring systems.

Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data.

UNLABELLED: Gemma is a database, analysis software system and web site for genomics data re-use and meta-analysis. Currently, Gemma contains analyzed data from over 3300 expression profiling studies, yielding hundreds of millions of differential expression results and coexpression patterns (correlated expression) for retrieval and visualization. With optional registration users can save their own data and securely share it with other users. Web services and integration with third-party resources further increase the scope of the tools, which include a Cytoscape plugin. AVAILABILITY: http://chibi.ubc.ca/Gemma, Apache 2.0 license.

SLIMS--a user-friendly sample operations and inventory management system for genotyping labs.

SUMMARY: We present the Sample-based Laboratory Information Management System (SLIMS), a powerful and user-friendly open source web application that provides all members of a laboratory with an interface to view, edit and create sample information. SLIMS aims to simplify common laboratory tasks with tools such as a user-friendly shopping cart for subjects, samples and containers that easily generates reports, shareable lists and plate designs for genotyping. Further key features include customizable data views, database change-logging and dynamically filled pre-formatted reports. Along with being feature-rich, SLIMS' power comes from being able to handle longitudinal data from multiple time-points and biological sources. This type of data is increasingly common from studies searching for susceptibility genes for common complex diseases that collect thousands of samples generating millions of genotypes and overwhelming amounts of data. LIMSs provide an efficient way to deal with this data while increasing accessibility and reducing laboratory errors; however, professional LIMS are often too costly to be practical. SLIMS gives labs a feasible alternative that is easily accessible, user-centrically designed and feature-rich. To facilitate system customization, and utilization for other groups, manuals have been written for users and developers. AVAILABILITY: Documentation, source code and manuals are available at http://genapha.icapture.ubc.ca/SLIMS/index.jsp. SLIMS was developed using Java 1.6.0, JSPs, Hibernate 3.3.1.GA, DB2 and mySQL, Apache Tomcat 6.0.18, NetBeans IDE 6.5, Jasper Reports 3.5.1 and JasperSoft's iReport 3.5.1.

Pseudomonas Genome Database: facilitating user-friendly, comprehensive comparisons of microbial genomes.

Pseudomonas aeruginosa is a well-studied opportunistic pathogen that is particularly known for its intrinsic antimicrobial resistance, diverse metabolic capacity, and its ability to cause life threatening infections in cystic fibrosis patients. The Pseudomonas Genome Database (http://www.pseudomonas.com) was originally developed as a resource for peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome. In order to facilitate cross-strain and cross-species genome comparisons with other Pseudomonas species of importance, we have now expanded the database capabilities to include all Pseudomonas species, and have developed or incorporated methods to facilitate high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. A choice of simple and more flexible user-friendly Boolean search features allows researchers to search and compare annotations or sequences within or between genomes. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. This database aims to continue to provide a high quality, annotated genome resource for the research community and is available under an open source license.

The Burkholderia Genome Database: facilitating flexible queries and comparative analyses.

UNLABELLED: As the genome sequences of multiple strains of a given bacterial species are obtained, more generalized bacterial genome databases may be complemented by databases that are focused on providing more information geared for a distinct bacterial phylogenetic group and its associated research community. The Burkholderia Genome Database represents a model for such a database, providing a powerful, user-friendly search and comparative analysis interface that contains features not found in other genome databases. It contains continually updated, curated and tracked information about Burkholderia cepacia complex genome annotations, plus other Burkholderia species genomes for comparison, providing a high-quality resource for its targeted cystic fibrosis research community. AVAILABILITY: http://www.burkholderia.com. Source code: GNU GPL.

Force-induced polarized mitosis of endothelial and smooth muscle cells in arterial remodeling.

Arteries display highly directional growth and remodeling that are specific to increases in the mechanical loads imposed on them by blood pressure, blood flow, and lengthwise tensile forces that are transmitted from the tissues to which they are attached. This study examined the effect of mechanical forces on the direction in which mitosis delivers daughter cells, as a mechanism for directional growth. Lateral forces were imposed on surface integrins of cultured endothelial cells by seeding the cells with arginine-glycine-aspartate peptide-coated magnetic microspheres and applying a magnetic field. Video images revealed that the mitotic axis of dividing cells became highly biased in the direction of applied force. Distribution of cortactin, which participates in polarized mitoses driven by other stimuli, was highly sensitive to mechanical loading and interfering with cortactin function arrested cell growth. Smooth muscle cell mitoses also proved to be sensitive to mechanical force: when lengthwise force imposed on rabbit carotid arteries was altered by excision of a vessel segment and reanastomosis of the cut ends, direction of mitosis was dramatically altered. These findings indicate that influences of mechanical force can modulate the manner in which mitosis of vascular cells contributes to reorganization of arterial wall tissue.