Organization Of Microbial Communities Research Articles

Tip extension and simultaneous multiple fission in a filamentous bacterium

Organisms display an immense variety of shapes, sizes, and reproductive strategies. At microscopic scales, bacterial cell morphology and growth dynamics are adaptive traits that influence the spatial organization of microbial communities. In one such community-the human dental plaque biofilm-a network of filamentous Corynebacterium matruchotii cells forms the core of bacterial consortia known as hedgehogs, but the processes that generate these structures are unclear. Here, using live-cell time-lapse microscopy and fluorescent D-amino acids to track peptidoglycan biosynthesis, we report an extraordinary example of simultaneous multiple division within the domain Bacteria. We show that C. matruchotii cells elongate at one pole through tip extension, similar to the growth strategy of soil-dwelling Streptomyces bacteria. Filaments elongate rapidly, at rates more than five times greater than other closely related bacterial species. Following elongation, many septa form simultaneously, and each cell divides into 3 to 14 daughter cells, depending on the length of the mother filament. The daughter cells then nucleate outgrowth of new thinner vegetative filaments, generating the classic "whip handle" morphology of this taxon. Our results expand the known diversity of bacterial cell cycles and help explain how this filamentous bacterium can compete for space, access nutrients, and form important interspecies interactions within dental plaque.

Adhesive interactions within microbial consortia can be differentiated at the single-cell level through expansion microscopy.

Investigating microbe-microbe interactions at the single-cell level is critical to unraveling the ecology and dynamics of microbial communities. In many situations, microbes assemble themselves into densely packed multi-species biofilms. The density and complexity pose acute difficulties for visualizing individual cells and analyzing their interactions. Here, we address this problem through an unconventional application of expansion microscopy, which allows for the 'decrowding' of individual bacterial cells within a multispecies community. Expansion microscopy generally has been carried out under isotropic expansion conditions and used as a resolution-enhancing method. In our variation of expansion microscopy, we carry out expansion under heterotropic conditions; that is, we expand the space between bacterial cells but not the space within individual cells. The separation of individual bacterial cells from each other reflects the competition between the expansion force pulling them apart and the adhesion force holding them together. We employed heterotropic expansion microscopy to study the relative strength of adhesion in model biofilm communities. These included mono and dual-species Streptococcus biofilms, and a three-species synthetic community (Fusobacterium nucleatum, Streptococcus mutans, and Streptococcus sanguinis) under conditions that facilitated interspecies coaggregation. Using adhesion mutants, we investigated the interplay between F. nucleatum outer membrane protein RadD and different Streptococcus species. We also examined the Schaalia-TM7 epibiont association. Quantitative proximity analysis was used to evaluate the separation of individual microbial members. Our study demonstrates that heterotropic expansion microscopy can 'decrowd' dense biofilm communities, improve visualization of individual bacterial members, and enable analysis of microbe-microbe adhesive interactions at the single-cell level.

Microbial community organization designates distinct pulmonary exacerbation types and predicts treatment outcome in cystic fibrosis

Polymicrobial infection of the airways is a hallmark of obstructive lung diseases such as cystic fibrosis (CF), non-CF bronchiectasis, and chronic obstructive pulmonary disease. Pulmonary exacerbations (PEx) in these conditions are associated with accelerated lung function decline and higher mortality rates. Understanding PEx ecology is challenged by high inter-patient variability in airway microbial community profiles. We analyze bacterial communities in 880 CF sputum samples collected during an observational prospective cohort study and develop microbiome descriptors to model community reorganization prior to and during 18 PEx. We identify two microbial dysbiosis regimes with opposing ecology and dynamics. Pathogen-governed PEx show hierarchical community reorganization and reduced diversity, whereas anaerobic bloom PEx display stochasticity and increased diversity. A simulation of antimicrobial treatment predicts better efficacy for hierarchically organized communities. This link between PEx, microbiome organization, and treatment success advances the development of personalized clinical management in CF and, potentially, other obstructive lung diseases.

Microbial Community Organization during Anaerobic Pulp and Paper Mill Wastewater Treatment

Microbial Community Organization during Anaerobic Pulp and Paper Mill Wastewater Treatment

Active Density Pattern Formation in Bacterial Binary Mixtures

Microbial communities often exhibit complex spatial structures that are important for their functioning, ecology, and evolution. While the role of biochemical interactions is extensively studied, how physical interactions contribute to structuring typically multispecies and phenotypically diverse bacterial communities is unclear. Here, we examined how motility, a major bacterial trait, affects the organization of model binary mixtures of motile and nonmotile bacteria, revealing a novel type of active self-organization. Motile bacteria induce large-scale, fluctuating density patterns in nonmotile bacteria across a wide range of physiologically relevant cell densities. Combining experiments and quantitative modeling, we demonstrate that this pattern formation solely results from physical interactions and relies on two key ingredients: By swimming in circles at surfaces, the motile bacteria generate recirculating hydrodynamic flows that advect nonmotile cells, and the breaking of vertical symmetry by gravity permits local density accumulation. The density patterns fluctuate as the advection landscape slowly rearrange with motile cells configurations on the surfaces. This new nonequilibrium mechanism for pattern formation in bacteria belongs to a different class compared to previous models for self-organization in self-propelled systems, which rely on localized traffic jamming in two dimensions. It is instead similar to fluctuation-dominated phase ordering in active nematics. The behavior also drives the formation of large scale and highly structured aggregates of nonmotile cells that express adhesins in the mixture, and it showcases how motile species activity can shape the spatial organization of complex microbial communities. Published by the American Physical Society 2024

Network Analysis Reveals Species-Specific Organization of Microbial Communities in Four Co-Occurring Elasmobranch Species along the Georgia Coast

Comparing co-occurring species may provide insights into how aspects of ecology may play a role in influencing their microbial communities. During the 2019 commercial shrimp trawl season off coastal Georgia, swabs of skin, gills, cloaca, and gut were taken for three species of batoids (Butterfly Ray, Bluntnose Stingray, and Atlantic Stingray) and one shark species (Atlantic Sharpnose) for high-throughput sequencing of the V4 region of the bacterial 16S rRNA gene. White muscle was analyzed for stable isotopes (δ13C and δ15N) to evaluate potential niche overlap in these four sympatric mesopredators. Significant differences were found in both δ13C and δ15N signatures across species, suggesting a degree of resource partitioning. When examined within tissue type, the host species had a weak effect on β-diversity for cloaca and skin, with no differences found for gill and gut samples. However, network analysis metrics demonstrated a stronger species-specific effect and distinct microbial community relationships were apparent between the shark and batoids, with the former having tighter networks for both internally- and externally-influenced tissues (gut/cloaca and skin/gills, respectively). Despite overlapping habitat use, species’ microbiomes differed in their organizational structuring that paralleled differences in stable isotope results, suggesting a mediating role of species-specific ecology on bacterial microbiomes.

The structure of microbial communities in redoximorphic microsites of Gleysol

AbstractMicrobial communities were studied in redoximorphic microsites of highly heterogeneous Gleysol at a mm scale using 16S and 18S amplicon sequencing to demonstrate if the composition of soil microbes reflects the differences in ferric and ferrous micro‐sites. In both explored gley horizons with redoximorphic features (Bg2 and Cg), ferric mottles were significantly enriched with total P and Fe and depleted of O, Si, Al, K and Ca compared with the adjacent ferrous groundmass (SEM–EDS). Ferric mottles were determined as Fe oxide coatings and hypocoatings. In Bg2, both prokaryotic and micro‐eukaryotic communities differed significantly between mottles and groundmass in composition of operational taxonomic units (OTUs) and in proportions of phyla, reflecting heterogeneities in the soil properties there. Mottles in Bg2 were characterized by increased proportion of Proteobacteria, decreased proportion of Acidobacteriota among prokaryotes and by dominance of a single proteobacterial OTU from Anaplasmataceae compared to all other samples. The composition of micro‐eukaryotes showed an opposite trend, as micro‐eukaryotes of Bg2 groundmass were unique among the other horizons, while micro‐eukaryotes of Bg2 mottles had similar composition to neighbouring horizons. Microbial communities of adjacent samples were not more similar to each other than communities of randomly selected ones in Bg2 horizon. That suggests that at mm scale, the sample distance does not represent the driving factor of microbial community composition and that the adjacent samples differ rather due to physicochemical factors. The spatial organization of microbial communities revealed in Bg2 has not reappeared in similarly organized Cg horizon, probably due to other overriding factors. The differences revealed between Bg2 and Cg horizons, including granulometric composition, content of crystalline Fe, exchangeable Al, and organic carbon, as well as exposition to groundwater, were discussed as possible reasons of the distinct organization in Cg. The similarity of pro−/eukaryotic communities of adjacent and non‐adjacent couples suggests no distance decay pattern at a mm scale. The agreement between patchiness in soil properties and microbial communities was revealed for the first time and confirms the importance of microscale patterns in soil.

Marine Fungi Select and Transport Aerobic and Anaerobic Bacterial Populations from Polycyclic Aromatic Hydrocarbon-Contaminated Sediments.

The organization of microbial communities in marine sediment relies on complex biotic and abiotic interactions. Among them, the interaction between fungi and bacteria plays a crucial role building specific microbial assemblages, resulting in metabolic networks adapted to environmental conditions. The fungal-bacterial interaction (FBI) includes bacterial translocation via fungal mycelia, allowing bacterial dispersion, and ecological niche colonization. In order to demonstrate that the translocation of bacteria through fungal mycelia involves bacterial selection, the mycelia of two fungi isolated from marine coastal sediment, Alternaria destruens F10.81 and Fusarium pseudonygamai F5.76, showing different strategies for uptake of polycyclic aromatic hydrocarbon (PAH), homogenous internalization and vacuole forming respectively, were used to translocate bacteria through hydrophobic hydrocarbon contaminated sediments. A. destruens F10.81 selected four specific bacteria, while bacterial selection by F. pseudonygamai F5.76 was not evident. Among the bacteria selected by A. destruens F10.81, Spirochaeta litoralis, known as strictly anaerobic bacterium, was identified, indicating that A. destruens F10.81 selects and transports both aerobic and anaerobic bacteria. Such a result is consistent with the observed formation of anoxic micro-niches in areas surrounding and affected by fungal hyphae. Our findings provide new insights on the selection and dispersion of bacterial communities by fungi, which are crucial for the organization of microbial communities and their functioning in coastal PAH-contaminated sediments. IMPORTANCE The study provides advances for understanding fungal-bacterial relationships, particularly on the selection and dispersion of bacterial communities by fungi, which are crucial for the organization of microbial communities and their functioning in coastal PAH-contaminated sediments. The transportation of bacteria via fungal hyphae (fungal highway) results in bacterial selection; in particular, fungal hyphae offer adequate conditions for the transport of both aerobic and anaerobic bacteria through hydrophobic patches for the colonization of novel niches.

Vertical organization of microbial communities in Salineta hypersaline wetland, Spain.

Microbial communities inhabiting hypersaline wetlands, well adapted to the environmental fluctuations due to flooding and desiccation events, play a key role in the biogeochemical cycles, ensuring ecosystem service. To better understand the ecosystem functioning, we studied soil microbial communities of Salineta wetland (NE Spain) in dry and wet seasons in three different landscape stations representing situations characteristic of ephemeral saline lakes: S1 soil usually submerged, S2 soil intermittently flooded, and S3 soil with halophytes. Microbial community composition was determined according to different redox layers by 16S rRNA gene barcoding. We observed reversed redox gradient, negative at the surface and positive in depth, which was identified by PERMANOVA as the main factor explaining microbial distribution. The Pseudomonadota, Gemmatimonadota, Bacteroidota, Desulfobacterota, and Halobacteriota phyla were dominant in all stations. Linear discriminant analysis effect size (LEfSe) revealed that the upper soil surface layer was characterized by the predominance of operational taxonomic units (OTUs) affiliated to strictly or facultative anaerobic halophilic bacteria and archaea while the subsurface soil layer was dominated by an OTU affiliated to Roseibaca, an aerobic alkali-tolerant bacterium. In addition, the potential functional capabilities, inferred by PICRUSt2 analysis, involved in carbon, nitrogen, and sulfur cycles were similar in all samples, irrespective of the redox stratification, suggesting functional redundancy. Our findings show microbial community changes according to water flooding conditions, which represent useful information for biomonitoring and management of these wetlands whose extreme aridity and salinity conditions are exposed to irreversible changes due to human activities.

Organization of Microbial Communities in Soils: Experiment with Fouling Glasses in Extreme Terrestrial Landscapes of Antarctica

Organization of Microbial Communities in Soils: Experiment with Fouling Glasses in Extreme Terrestrial Landscapes of Antarctica

The contrasting roles of nitric oxide drive microbial community organization as a function of oxygen presence

Microbial assemblages are omnipresent in the biosphere, forming communities on the surfaces of roots and rocks and within living tissues. These communities can exhibit strikingly beautiful compositional structures, with certain members reproducibly occupying particular spatiotemporal microniches. Despite this reproducibility, we lack the ability to explain these spatial patterns. We hypothesize that certain spatial patterns in microbial communities may be explained by the exchange of redox-active metabolites whose biological function is sensitive to microenvironmental gradients. To test this, we developed a simple community consisting of synthetic Pseudomonas aeruginosa strains with a partitioned denitrification pathway: a strict consumer and strict producer of nitric oxide (NO), a key pathway intermediate. Because NO can be both toxic or beneficial depending on the amount of oxygen present, this system provided an opportunity to investigate whether dynamic oxygen gradients can tune metabolic cross-feeding and fitness outcomes in a predictable fashion. Using a combination of genetic analysis, controlled growth environments, and imaging, we show that oxygen availability dictates whether NO cross-feeding is deleterious or mutually beneficial and that this organizing principle maps to the microscale. More generally, this work underscores the importance of considering the double-edged and microenvironmentally tuned roles redox-active metabolites can play in shaping microbial communities.

Feeding by heterotrophic flagellates on marine archaea

Archaea live in diverse habitats including extreme environments. Although they are sometimes the dominant heterotrophic organisms in microbial communities, relatively little is known about their ecological roles in microbial food webs. To explore predator–prey relationships between archaea and heterotrophic protists, we determined feeding occurrence by the heterotrophic nanoflagellates Bodo sp., Goniomonas sp., and Pedospumella sp. the common heterotrophic dinoflagellates Cryptoperidiniopsis brodyi, Gyrodinium dominans, Oblea rotunda, Oxyrrhis marina, and Polykrikos kofoidii on ammonia-oxidizing archaea (AOA) by examining the food vacuoles of these heterotrophic flagellates under an epifluorescence microscope using fluorescently labeled AOA. In addition, we measured the ingestion rates of Goniomonas sp., C. brodyi, G.dominans, and O. marina on AOA as a function of prey concentration. Cells of Bodo sp., Goniomonas sp., Pedospumella sp., C. brodyi, G.dominans, and O. marina were able to feed on AOA, whereas O. rotunda and P. kofoidii were not. With increasing initial prey concentration up to 1.7 × 106 – 9.3 × 106 cells mL−1, the ingestion rates of Goniomonas sp., C. brodyi, G.dominans, and O. marina on AOA increased rapidly but increased slowly or became saturated at higher concentrations. Although the maximum ingestion rates of the smaller flagellate Goniomonas sp. (23.1 cells predator−1 h−1) on AOA was much lower than that of the larger flagellate O. marina (296.4 cells predator−1 h−1), AOA supported the positive growth of only Goniomonas sp. The results of the present study suggest that these small heterotrophic flagellates could be effective heterotrophic protist grazers of AOA in marine ecosystems.

The Lumenal Microbiota Varies Biogeographically in the Gastrointestinal Tract of Rhesus Macaques.

ABSTRACTThe strategy of adjusting the composition of gastrointestinal microbiota has shown great promise for the treatment of diseases. Currently, the relationship between gut microbes and human diseases is mainly presented by the fecal microbiota from the colon. Due to the limits of sampling, the healthy baseline of biogeographic microbiota in the human gastrointestinal tract remains blurry. Captive nonhuman primates (NHPs) present a “humanized” intestinal microbiome and may make up for the lack of atlas data for better understanding of the gut microbial composition and diseases. Therefore, the intestinal microbiota of 6 GIT regions of healthy rhesus monkeys were analyzed in this study; our results showed that Proteobacteria gradually decreased from the small intestine to the large intestine but Bacteroidetes gradually increased from the small intestine to the large intestine. Streptococcus and Lactobacillus can be used as markers to distinguish the small intestine from the large intestine. Sarcina is the most enriched in the middle site of the connection between the large intestine and the small intestine. Cyanobacteria are enriched in the small intestine, especially the duodenum and jejunum, and are absent in the large intestine. The lumenal microbiota of the small intestine is more susceptible to individual differences than is that of the large intestine. Metabolism and oxygen affect the distribution of the microbes, and the diversity of microbiota is the highest in the colon. Our results provide accurate comprehensive GIT microbiota data on nonhuman primates and will be beneficial for the better understanding of the composition of microbiota in the human gastrointestinal tract.IMPORTANCE For the study of upper gastrointestinal microbiota in humans, endoscopic sampling is the main source of information, which limits the understanding of healthy upper gastrointestinal microbiota. Rhesus monkeys show very close similarity to humans in physiology, genetics, and behavior and act as the most suitable animal models for human diseases. The present research made up for the lack of atlas data due to the ethical limitations of sampling in humans and provided baseline data on microbiota in 6 GIT regions of healthy NHPs. These important references will be beneficial for the better understanding of the regional organization and functions of gut microbial communities along the GIT and their relevance to conditions of health and disease.

Three-dimensional imaging for the quantification of spatial patterns in microbiota of the intestinal mucosa

Improving our understanding of host–microbe relationships in the gut requires the ability to both visualize and quantify the spatial organization of microbial communities in their native orientation with the host tissue. We developed a systematic procedure to quantify the three-dimensional (3D) spatial structure of the native mucosal microbiota in any part of the intestines with taxonomic and high spatial resolution. We performed a 3D biogeographical analysis of the microbiota of mouse cecal crypts at different stages of antibiotic exposure. By tracking eubacteria and four dominant bacterial taxa, we found that the colonization of crypts by native bacteria is a dynamic and spatially organized process. Ciprofloxacin treatment drastically reduced bacterial loads and eliminated Muribaculaceae (or all Bacteroidetes entirely) even 10 d after recovery when overall bacterial loads returned to preantibiotic levels. Our 3D quantitative imaging approach revealed that the bacterial colonization of crypts is organized in a spatial pattern that consists of clusters of adjacent colonized crypts that are surrounded by unoccupied crypts, and that this spatial pattern is resistant to the elimination of Muribaculaceae or of all Bacteroidetes by ciprofloxacin. Our approach also revealed that the composition of cecal crypt communities is diverse and that Lactobacilli were found closer to the lumen than Bacteroidetes, Ruminococcaceae, and Lachnospiraceae, regardless of antibiotic exposure. Finally, we found that crypts communities with similar taxonomic composition were physically closer to each other than communities that were taxonomically different.

Statistical Methods for Microbiome Compositional Data Network Inference: A Survey

Microbes can be found almost everywhere in the world. They are not isolated, but rather interact with each other and establish connections with their living environments. Studying these interactions is essential to an understanding of the organization and complex interplay of microbial communities, as well as the structure and dynamics of various ecosystems. A widely used approach toward this objective involves the inference of microbiome interaction networks. However, owing to the compositional, high-dimensional, sparse, and heterogeneous nature of observed microbial data, applying network inference methods to estimate their associations is challenging. In addition, external environmental interference and biological concerns also make it more difficult to deal with the network inference. In this article, we provide a comprehensive review of emerging microbiome interaction network inference methods. According to various research targets, estimated networks are divided into four main categories: correlation networks, conditional correlation networks, mixture networks, and differential networks. Their assumptions, high-level ideas, advantages, as well as limitations, are presented in this review. Since real microbial interactions can be complex and dynamic, no unifying method has, to date, captured all the aspects of interest. In addition, we discuss the challenges now confronting current microbial interaction study and future prospects. Finally, we point out several feasible directions of microbial network inference analysis and highlight that future research requires the joint promotion of statistical computation methods and experimental techniques.

Network-based approaches for the investigation of microbial community structure and function using metagenomics-based data.

Network-based approaches offer a powerful framework to evaluate microbial community organization and function as it relates to a variety of environmental processes. Emerging studies are exploring network theory as a method for data integration that is likely to be critical forthe integration of 'omics' data using systems biology approaches. Intricacies of network theory and methodological and computational complexities in network construction, however, impede the use of these tools for translational science. We provide a perspective on the methods of network construction, interpretationand emerging uses for these techniques in understanding host-microbiota interactions.

INAP: An integrated network analysis pipeline for microbiome studies.

Integrated network analysis pipeline (iNAP) is an online analysis pipeline for generating and analyzing comprehensive ecological networks in microbiome studies. It is implemented in two sections, that is, network construction and network analysis, and integrates many open-access tools. Network construction contains multiple feasible alternatives, including correlation-based approaches (Pearson's correlation and Spearman's rank correlation along with random matrix theory, and sparse correlations for compositional data) and conditional dependence-based methods (extended local similarity analysis and sparse inverse covariance estimation for ecological association inference), while network analysis provides topological structures at different levels and the potential effects of environmental factors on network structures. Considering the full workflow, from microbiome data set to network result, iNAP contains the molecular ecological network analysis pipeline and interdomain ecological network analysis pipeline (IDENAP), which correspond to the intradomain and interdomain associations of microbial species at multiple taxonomic levels. Here, we describe the detailed workflow by taking IDENAP as an example and show the comprehensive steps to assist researchers to conduct the relevant analyses using their own data sets. Afterwards, some auxiliary tools facilitating the pipeline are introduced to effectively aid in the switch from local analysis to online operations. Therefore, iNAP, as an easy-to-use platform that provides multiple network-associated tools and approaches, can enable researchers to better understand the organization of microbial communities. iNAP is available at http://mem.rcees.ac.cn:8081 with free registration.

Microbial communities in soil macro-aggregates with less connected networks respire less across successional and geographic gradients

The formation of soil aggregates is related to the stability of soil organic carbon, which distinguishes the living conditions of microbial communities in different micro-niches. Here, we investigated fungal and bacterial community structure, networks, biomass and respiration in individual micro-niches between and within soil aggregates using seven different chronosequences (both primary and secondary successions from pioneer stages to well-developed ecosystems) on a European-scale gradient from a maritime climate in Belgium to a more continental climate in Hungary. We showed that geographical location was the most important factor (74% for bacterial community, 53% for fungal community) affecting microbial community composition, while soil aggregates (5% for bacterial community and 12% for fungal community) were the second most important factor followed by age of succession and vegetation. Moreover, aggregates (52%) were the most important factor influencing the biomass of major microbial groups, followed by location (37%) and age of succession (6%). Interestingly, macro-aggregates had less interconnected microbial networks and low microbial respiration rates compared to other aggregate sizes. We therefore hypothesize that the embedding of organic particles in the mineral matrix of macro-aggregates is a crucial point in microbial community organization, as evidenced by microbial community connectivity and microbial respiration. Our results demonstrate the importance of soil aggregates for microbial community organization and soil carbon stabilization.

Species- and site-specific genome editing in complex bacterial communities.

Understanding microbial gene functions relies on the application of experimental genetics in cultured microorganisms. However, the vast majority of bacteria and archaea remain uncultured, precluding the application of traditional genetic methods to these organisms and their interactions. Here, we characterize and validate a generalizable strategy for editing the genomes of specific organisms in microbial communities. We apply environmental transformation sequencing (ET-seq), in which nontargeted transposon insertions are mapped and quantified following delivery to a microbial community, to identify genetically tractable constituents. Next, DNA-editing all-in-one RNA-guided CRISPR-Cas transposase (DART) systems for targeted DNA insertion into organisms identified as tractable by ET-seq are used to enable organism- and locus-specific genetic manipulation in a community context. Using a combination of ET-seq and DART in soil and infant gut microbiota, we conduct species- and site-specific edits in several bacteria, measure gene fitness in a nonmodel bacterium and enrich targeted species. These tools enable editing of microbial communities for understanding and control.

Analytics and visualization tools to characterize single-cell stochasticity using bacterial single-cell movie cytometry data

BackgroundTime-lapse microscopy live-cell imaging is essential for studying the evolution of bacterial communities at single-cell resolution. It allows capturing detailed information about the morphology, gene expression, and spatial characteristics of individual cells at every time instance of the imaging experiment. The image analysis of bacterial "single-cell movies" (videos) generates big data in the form of multidimensional time series of measured bacterial attributes. If properly analyzed, these datasets can help us decipher the bacterial communities' growth dynamics and identify the sources and potential functional role of intra- and inter-subpopulation heterogeneity. Recent research has highlighted the importance of investigating the role of biological "noise" in gene regulation, cell growth, cell division, etc. Single-cell analytics of complex single-cell movie datasets, capturing the interaction of multiple micro-colonies with thousands of cells, can shed light on essential phenomena for human health, such as the competition of pathogens and benign microbiome cells, the emergence of dormant cells (“persisters”), the formation of biofilms under different stress conditions, etc. However, highly accurate and automated bacterial bioimage analysis and single-cell analytics methods remain elusive, even though they are required before we can routinely exploit the plethora of data that single-cell movies generate.ResultsWe present visualization and single-cell analytics using R (ViSCAR), a set of methods and corresponding functions, to visually explore and correlate single-cell attributes generated from the image processing of complex bacterial single-cell movies. They can be used to model and visualize the spatiotemporal evolution of attributes at different levels of the microbial community organization (i.e., cell population, colony, generation, etc.), to discover possible epigenetic information transfer across cell generations, infer mathematical and statistical models describing various stochastic phenomena (e.g., cell growth, cell division), and even identify and auto-correct errors introduced unavoidably during the bioimage analysis of a dense movie with thousands of overcrowded cells in the microscope's field of view.ConclusionsViSCAR empowers researchers to capture and characterize the stochasticity, uncover the mechanisms leading to cellular phenotypes of interest, and decipher a large heterogeneous microbial communities' dynamic behavior. ViSCAR source code is available from GitLab at https://gitlab.com/ManolakosLab/viscar.