A functional perspective on phenotypic heterogeneity in microorganisms

Transcription in fungal conidia before dormancy produces phenotypically variable conidia that maximize survival in different environments

Fungi produce millions of clonal asexual conidia (spores) that remain dormant until favourable conditions occur. Conidia contain abundant stable messenger RNAs but the mechanisms underlying the production of these transcripts and their composition and functions are unknown. Here, we report that the conidia of three filamentous fungal species (Aspergillus nidulans, Aspergillus fumigatus, Talaromyces marneffei) are transcriptionally active and can synthesize mRNAs. We find that transcription in fully developed conidia is modulated in response to changes in the environment until conidia leave the developmental structure. Environment-specific transcriptional responses can alter conidial content (mRNAs, proteins and secondary metabolites) and change gene expression when dormancy is broken. Conidial transcription affects the fitness and capabilities of fungal cells after germination, including stress and antifungal drug (azole) resistance, mycotoxin and secondary metabolite production and virulence. The transcriptional variation that we characterize in fungal conidia explains how genetically identical conidia mature into phenotypically variable conidia. We find that fungal conidia prepare for the future by synthesizing and storing transcripts according to environmental conditions present before dormancy.

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.

Quorum sensing governs a transmissive Legionella subpopulation at the pathogen vacuole periphery

The Gram‐negative bacterium Legionella pneumophila is the causative agent of Legionnaires' disease and replicates in amoebae and macrophages within a distinct compartment, the Legionella‐containing vacuole (LCV). The facultative intracellular pathogen switches between a replicative, non‐virulent and a non‐replicating, virulent/transmissive phase. Here, we show on a single‐cell level that at late stages of infection, individual motile (P_flaA‐GFP‐positive) and virulent (P_ralF‐ and P_sidC‐GFP‐positive) L. pneumophila emerge in the cluster of non‐growing bacteria within an LCV. Comparative proteomics of P_flaA‐GFP‐positive and P_flaA‐GFP‐negative L. pneumophila subpopulations reveals distinct proteomes with flagellar proteins or cell division proteins being preferentially produced by the former or the latter, respectively. Toward the end of an infection cycle (˜ 48 h), the P_flaA‐GFP‐positive L. pneumophila subpopulation emerges at the cluster periphery, predominantly escapes the LCV, and spreads from the bursting host cell. These processes are mediated by the Legionella quorum sensing (Lqs) system. Thus, quorum sensing regulates the emergence of a subpopulation of transmissive L. pneumophila at the LCV periphery, and phenotypic heterogeneity underlies the intravacuolar bi‐phasic life cycle of L. pneumophila.

Temporal fluctuations in chemotaxis gain implement a simulated-tempering strategy for efficient navigation in complex environments

Bacterial chemotaxis is a major testing ground for systems biology, including the role of fluctuations and individual variation. Individual bacteria vary in their tumbling frequency and adaptation time. Recently, large cell-cell variation was also discovered in chemotaxis gain, which determines the sensitivity of the tumbling rate to attractant gradients. Variation in gain is puzzling, because low gain impairs chemotactic velocity. Here, we provide a functional explanation for gain variation by establishing a formal analogy between chemotaxis and algorithms for sampling probability distributions. We show that temporal fluctuations in gain implement simulated tempering, which allows sampling of attractant distributions with many local peaks. Periods of high gain allow bacteria to detect and climb gradients quickly, and periods of low gain allow them to move to new peaks. Gain fluctuations thus allow bacteria to thrive in complex environments, and more generally they may play an important functional role for organism navigation.

Single-Cell RNA Sequencing Elucidates the Structure and Organization of Microbial Communities

Clonal bacterial populations exhibit various forms of heterogeneity, including co-occurrence of cells with different morphological traits, biochemical properties, and gene expression profiles. This heterogeneity is prevalent in a variety of environments. For example, the productivity of large-scale industrial fermentations and virulence of infectious diseases are shaped by cell population heterogeneity and have a direct impact on human life. Due to the need and importance to better understand this heterogeneity, multiple methods of examining single-cell heterogeneity have been developed. Traditionally, fluorescent reporters or probes are used to examine a specific gene of interest, providing a useful but inherently biased approach. In contrast, single-cell RNA sequencing (scRNA-seq) is an agnostic approach to examine heterogeneity and has been successfully applied to eukaryotic cells. Unfortunately, current extensively utilized methods of eukaryotic scRNA-seq present difficulties when applied to bacteria. Specifically, bacteria have a cell wall which makes eukaryotic lysis methods incompatible, bacterial mRNA has a shorter half-life and lower copy numbers, and isolating an individual bacterial species from a mixed community is difficult. Recent work has demonstrated that these technical hurdles can be overcome, providing valuable insight into factors influencing microbial heterogeneity. This perspective describes the emerging microbial scRNA-seq toolkit. We outline the benefit of these new tools in elucidating numerous scientific questions in microbiological studies and offer insight about the possible rules that govern the segregation of traits in individual microbial cells.

Phenotypic plasticity through disposable genetic adaptation in ciliates

Ciliates have an extraordinary genetic system in which each cell harbors two distinct kinds of nucleus, a transcriptionally active somatic nucleus and a quiescent germline nucleus. The latter undergoes classical, heritable genetic adaptation, while adaptation of the somatic nucleus is only short-term and thus disposable. The ecological and evolutionary relevance of this nuclear dimorphism have never been well formalized, which is surprising given the long history of using ciliates such as Tetrahymena and Paramecium as model organisms. We present a novel, alternative explanation for ciliate nuclear dimorphism which, we argue, should be considered an instrument of phenotypic plasticity by somatic selection on the level of the ciliate clone, as if it were a diffuse multicellular organism. This viewpoint helps to put some enigmatic aspects of ciliate biology into perspective and presents the diversity of ciliates as a large natural experiment that we can exploit to study phenotypic plasticity and organismality.

Diversity and Evolution of Clostridium beijerinckii and Complete Genome of the Type Strain DSM 791T

Clostridium beijerinckii is a relatively widely studied, yet non-model, bacterium. While 246 genome assemblies of its various strains are available currently, the diversity of the whole species has not been studied, and it has only been analyzed in part for a missing genome of the type strain. Here, we sequenced and assembled the complete genome of the type strain Clostridium beijerinckii DSM 791T, composed of a circular chromosome and a circular megaplasmid, and used it for a comparison with other genomes to evaluate diversity and capture the evolution of the whole species. We found that strains WB53 and HUN142 were misidentified and did not belong to the Clostridium beijerinckii species. Additionally, we filtered possibly misassembled genomes, and we used the remaining 237 high-quality genomes to define the pangenome of the whole species. By its functional annotation, we showed that the core genome contains genes responsible for basic metabolism, while the accessory genome has genes affecting final phenotype that may vary among different strains. We used the core genome to reconstruct the phylogeny of the species and showed its great diversity, which complicates the identification of particular strains, yet hides possibilities to reveal hitherto unreported phenotypic features and processes utilizable in biotechnology.

High concentrations of dissolved biogenic methane associated with cyanobacterial blooms in East African lake surface water

The contribution of oxic methane production to greenhouse gas emissions from lakes is globally relevant, yet uncertainties remain about the levels up to which methanogenesis can counterbalance methanotrophy by leading to CH₄ oversaturation in productive surface waters. Here, we explored the biogeochemical and microbial community variation patterns in a meromictic soda lake, in the East African Rift Valley (Kenya), showing an extraordinarily high concentration of methane in oxic waters (up to 156 µmol L⁻¹). Vertical profiles of dissolved gases and their isotopic signature indicated a biogenic origin of CH₄. A bloom of Oxyphotobacteria co-occurred with abundant hydrogenotrophic and acetoclastic methanogens, mostly found within suspended aggregates promoting the interactions between Bacteria, Cyanobacteria, and Archaea. Moreover, aggregate sedimentation appeared critical in connecting the lake compartments through biomass and organic matter transfer. Our findings provide insights into understanding how hydrogeochemical features of a meromictic soda lake, the origin of carbon sources, and the microbial community profiles, could promote methane oversaturation and production up to exceptionally high rates.

Fazi et al. report on an extraordinarily high biogenic methane concentration detected in the surface water of Lake Sonachi, Kenya. Using gas chromatography and microbiome profiling, they determine that these high concentrations are associated with cyanobacterial blooms and help provide insight to methanogenesis in meromictic soda lakes.

Non-Genetic Diversity in Chemosensing and Chemotactic Behavior

Non-genetic phenotypic diversity plays a significant role in the chemotactic behavior of bacteria, influencing how populations sense and respond to chemical stimuli. First, we review the molecular mechanisms that generate phenotypic diversity in bacterial chemotaxis. Next, we discuss the functional consequences of phenotypic diversity for the chemosensing and chemotactic performance of single cells and populations. Finally, we discuss mechanisms that modulate the amount of phenotypic diversity in chemosensory parameters in response to changes in the environment.

Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations

Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis.

Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics

Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.

Waddington's Landscapes in the Bacterial World

Conrad Waddington’s epigenetic landscape, a visual metaphor for the development of multicellular organisms, is appropriate to depict the formation of phenotypic variants of bacterial cells. Examples of bacterial differentiation that result in morphological change have been known for decades. In addition, bacterial populations contain phenotypic cell variants that lack morphological change, and the advent of fluorescent protein technology and single-cell analysis has unveiled scores of examples. Cell-specific gene expression patterns can have a random origin or arise as a programmed event. When phenotypic cell-to-cell differences are heritable, bacterial lineages are formed. The mechanisms that transmit epigenetic states to daughter cells can have strikingly different levels of complexity, from the propagation of simple feedback loops to the formation of complex DNA methylation patterns. Game theory predicts that phenotypic heterogeneity can facilitate bacterial adaptation to hostile or unpredictable environments, serving either as a division of labor or as a bet hedging that anticipates future challenges. Experimental observation confirms the existence of both types of strategies in the bacterial world.

Tracking bacterial lineages in complex and dynamic environments with applications for growth control and persistence

As bacteria transition from exponential to stationary phase, they change substantially in size, morphology, growth and expression profiles. These responses also vary between individual cells, but it has proved difficult to track cell lineages along the growth curve to determine the progression of events or correlations between how individual cells enter and exit dormancy. Here, we developed a platform for tracking more than 10⁵ parallel cell lineages in dense and changing cultures, independently validating that the imaged cells closely track batch populations. Initial applications show that for both Escherichia coli and Bacillus subtilis, growth changes from an 'adder' mode in exponential phase to mixed 'adder-timers' entering stationary phase, and then a near-perfect 'sizer' upon exit-creating broadly distributed cell sizes in stationary phase but rapidly returning to narrowly distributed sizes upon exit. Furthermore, cells that undergo more divisions when entering stationary phase suffer reduced survival after long periods of dormancy but are the only cells observed that persist following antibiotic treatment.

On-Chip Multicolor Photoacoustic Imaging Flow Cytometry

On-chip imaging flow cytometry has been widely used in cancer biology, immunology, microbiology, and drug discovery. Pure optical imaging combined with flow cytometry to derive chemical, structural, and morphological features of cells provides systematic insights into biological processes. However, due to the high concentration and strong optical attenuation of red blood cells, preprocessing is necessary for optical flow cytometry while dealing with whole blood. In this study, we develop an on-chip photoacoustic imaging flow cytometry (PAIFC), which combines multicolor high-speed photoacoustic microscopy and microfluidics for cell imaging. The device employs a micro-optical scanner to achieve a miniaturized outer size of 30 × 17 × 24 mm³ and ultrafast cross-sectional imaging at a frame rate of 1758 Hz and provides lateral and axial resolutions of 2.2 and 33 μm, respectively. Using a multicolor strategy, PAIFC is able to differentiate cells labeled by external contrast agents, detect melanoma cells with an endogenous contrast in whole blood, and image melanoma cells in blood samples from tumor-bearing mice. The results suggest that PAIFC has sufficient sensitivity and specificity for future cell-on-chip applications.

Mycobacterial Populations Partly Change the Proportions of the Cells Undergoing Asymmetric/Symmetric Divisions in Response to Glycerol Levels in Growth Medium

Twenty to thirty percent of the septating mycobacterial cells of the mid-log phase population showed highly deviated asymmetric constriction during division (ACD), while the remaining underwent symmetric constriction during division (SCD). The ACD produced short-sized cells (SCs) and normal/long-sized cells (NCs) as the sister-daughter cells, but with significant differential susceptibility to antibiotic/oxidative/nitrite stress. Here we report that, at 0.2% glycerol, formulated in the Middlebrook 7H9 medium, a significantly high proportion of the cells were divided by SCD. When the glycerol concentration decreased to 0.1% due to cell-growth/division, the ACD proportion gradually increased until the ACD:SCD ratio reached ~50:50. With further decrease in the glycerol levels, the SCD proportion increased with concomitant decrease in the ACD proportion. Maintenance of glycerol at 0.1%, through replenishment, held the ACD:SCD proportion at ~50:50. Transfer of the cells from one culture with a specific glycerol level to the supernatant from another culture, with a different glycerol level, made the cells change the ACD:SCD proportion to that of the culture from which the supernatant was taken. RT-qPCR data showed the possibility of diadenosine tetraphosphate phosphorylase (MSMEG_2932), phosphatidylinositol synthase (MSMEG_2933), and a Nudix family hydrolase (MSMEG_2936) involved in the ACD:SCD proportion-change in response to glycerol levels. We also discussed its physiological significance.

How to characterize a strain? Clonal heterogeneity in industrial Saccharomyces influences both phenotypes and heterogeneity in phenotypes

Populations of microbes are constantly evolving heterogeneity that selection acts upon, yet heterogeneity is nontrivial to assess methodologically. The necessary practice of isolating single-cell colonies and thus subclone lineages for establishing, transferring, and using a strain results in single-cell bottlenecks with a generally neglected effect on the characteristics of the strain itself. Here, we present evidence that various subclone lineages for industrial yeasts sequenced for recent genomic studies show considerable differences, ranging from loss of heterozygosity to aneuploidies. Subsequently, we assessed whether phenotypic heterogeneity is also observable in industrial yeast, by individually testing subclone lineages obtained from products. Phenotyping of industrial yeast samples and their newly isolated subclones showed that single-cell bottlenecks during isolation can indeed considerably influence the observable phenotype. Next, we decoupled fitness distributions on the level of individual cells from clonal interference by plating single-cell colonies and quantifying colony area distributions. We describe and apply an approach using statistical modeling to compare the heterogeneity in phenotypes across samples and subclone lineages. One strain was further used to show how individual subclonal lineages are remarkably different not just in phenotype but also in the level of heterogeneity in phenotype. With these observations, we call attention to the fact that choosing an initial clonal lineage from an industrial yeast strain may vastly influence downstream performances and observations on karyotype, on phenotype, and also on heterogeneity.

A microscopy-compatible temperature regulation system for single-cell phenotype analysis - demonstrated by thermoresponse mapping of microalgae

This work describes a programmable heat-stage compatible with in situ microscopy for the accurate provision of spatiotemporally defined temperatures to different microfluidic devices. The heat-stage comprises an array of integrated thin-film Joule heaters and resistance temperature detectors (RTDs). External programming of the heat-stage is provided by a custom software program connected to temperature controllers and heater-sensor pairs. Biologically relevant (20-40 °C) temperature profiles can be supplied to cells within microfluidic devices as spatial gradients (0.5-1.5 °C mm-1) or in a time-varying approach via e.g. step-wise or sinusoidally varying profiles with negligible temperature over-shoot. Demonstration of the device is achieved by exposing two strains of the coral symbiont Symbiodinium to different temperature profiles while monitoring their single-cell photophysiology via chlorophyll fluorometry. This revealed that photophysiological responses to temperature depended on the exposure duration, exposure magnitude and strain background. Moreover, thermal dose analysis suggested that cell acclimatisation occurs under longer temperature (6 h) exposures but not under shorter temperature exposures (15 min). As the thermal sensitivity of Symbiodinium mediates the thermal tolerance in corals, our versatile technology now provides unique possibilities to research this interdependency at single cell resolution. Our results also show the potential of this heat-stage for further applications in fields such as biotechnology and ecotoxicology.

Does Cancer Biology Rely on Parrondo's Principles?

Simple Summary

Parrondo’s paradox, whereby losing strategies or deleterious effects can combine to provide a winning outcome, has been increasingly applied by biologists to explain complex adaptations in many living systems. Here, we suggest that considering this paradox in oncology, particularly in relation to the phenotypic diversity of malignant cells, could also be a promising approach to understand several puzzling aspects of cancer biology. For example, the high genetic and epigenetic instability of cancer cells, their metastatic behavior and their capacity to enter dormancy could be explained by Parrondo’s theory. We also discuss the relevance of Parrondo’s paradox in a therapeutical framework using different examples. This work provides a compelling argument that the traditional separation between medicine and other disciplines remains a fundamental limitation that needs to be overcome if complex processes, such as oncogenesis, are to be completely understood.

Abstract

Many aspects of cancer biology remain puzzling, including the proliferative and survival success of malignant cells in spite of their high genetic and epigenetic instability as well as their ability to express migrating phenotypes and/or enter dormancy despite possible fitness loss. Understanding the potential adaptive value of these phenotypic traits is confounded by the fact that, when considered separately, they seem to be rather detrimental at the cell level, at least in the short term. Here, we argue that cancer’s biology and success could frequently be governed by processes underlying Parrondo’s paradox, whereby combinations of intrinsically losing strategies may result in winning outcomes. Oncogenic selection would favor Parrondo’s dynamics because, given the environmental adversity in which malignant cells emerge and evolve, alternating between various less optimal strategies would represent the sole viable option to counteract the changing and deleterious environments cells are exposed to during tumorigenesis. We suggest that malignant processes could be viewed through this lens, and we discuss how Parrondo’s principles are also important when designing therapies against cancer.

Cryptic surface-associated multicellularity emerges through cell adhesion and its regulation

The repeated evolution of multicellularity led to a wide diversity of organisms, many of which are sessile, including land plants, many fungi, and colonial animals. Sessile organisms adhere to a surface for most of their lives, where they grow and compete for space. Despite the prevalence of surface-associated multicellularity, little is known about its evolutionary origin. Here, we introduce a novel theoretical approach, based on spatial lineage tracking of cells, to study this origin. We show that multicellularity can rapidly evolve from two widespread cellular properties: cell adhesion and the regulatory control of adhesion. By evolving adhesion, cells attach to a surface, where they spontaneously give rise to primitive cell collectives that differ in size, life span, and mode of propagation. Selection in favor of large collectives increases the fraction of adhesive cells until a surface becomes fully occupied. Through kin recognition, collectives then evolve a central-peripheral polarity in cell adhesion that supports a division of labor between cells and profoundly impacts growth. Despite this spatial organization, nascent collectives remain cryptic, lack well-defined boundaries, and would require experimental lineage tracking technologies for their identification. Our results suggest that cryptic multicellularity could readily evolve and originate well before multicellular individuals become morphologically evident.

Generation of Genetic Tools for Gauging Multiple-Gene Expression at the Single-Cell Level

Key microbial processes in many bacterial species are heterogeneously expressed in single cells of bacterial populations. However, the paucity of adequate molecular tools for live, real-time monitoring of multiple-gene expression at the single-cell level has limited the understanding of phenotypic heterogeneity. To investigate phenotypic heterogeneity in the ubiquitous opportunistic pathogen Pseudomonas aeruginosa, a genetic tool that allows gauging multiple-gene expression at the single-cell level has been generated. This tool, named pRGC, consists of a promoter-probe vector for transcriptional fusions that carries three reporter genes coding for the fluorescent proteins mCherry, green fluorescent protein (GFP), and cyan fluorescent protein (CFP). The pRGC vector has been characterized and validated via single-cell gene expression analysis of both constitutive and iron-regulated promoters, showing clear discrimination of the three fluorescence signals in single cells of a P. aeruginosa population without the need for image processing for spectral cross talk correction. In addition, two pRGC variants have been generated for either (i) integration of the reporter gene cassette into a single neutral site of P. aeruginosa chromosome that is suitable for long-term experiments in the absence of antibiotic selection or (ii) replication in bacterial genera other than Pseudomonas The easy-to-use genetic tools generated in this study will allow rapid and cost-effective investigation of multiple-gene expression in populations of environmental and pathogenic bacteria, hopefully advancing the understanding of microbial phenotypic heterogeneity.IMPORTANCE Within a bacterial population, single cells can differently express some genes, even though they are genetically identical and experience the same chemical and physical stimuli. This phenomenon, known as phenotypic heterogeneity, is mainly driven by gene expression noise and results in the emergence of bacterial subpopulations with distinct phenotypes. The analysis of gene expression at the single-cell level has shown that phenotypic heterogeneity is associated with key bacterial processes, including competence, sporulation, and persistence. In this study, new genetic tools have been generated that allow easy cloning of up to three promoters upstream of distinct fluorescent genes, making it possible to gauge multiple-gene expression at the single-cell level by fluorescence microscopy without the need for advanced image-processing procedures. A proof of concept has been provided by investigating iron uptake and iron storage gene expression in response to iron availability in P. aeruginosa.

Elevated Expression of Toxin TisB Protects Persister Cells against Ciprofloxacin but Enhances Susceptibility to Mitomycin C

Bacterial chromosomes harbor toxin-antitoxin (TA) systems, some of which are implicated in the formation of multidrug-tolerant persister cells. In Escherichia coli, toxin TisB from the tisB/istR-1 TA system depolarizes the inner membrane and causes ATP depletion, which presumably favors persister formation. Transcription of tisB is induced upon DNA damage due to activation of the SOS response by LexA degradation. Transcriptional activation of tisB is counteracted on the post-transcriptional level by structural features of tisB mRNA and RNA antitoxin IstR-1. Deletion of the regulatory RNA elements (mutant Δ1-41 ΔistR) uncouples TisB expression from LexA-dependent SOS induction and causes a 'high persistence' (hip) phenotype upon treatment with different antibiotics. Here, we demonstrate by the use of fluorescent reporters that TisB overexpression in mutant Δ1-41 ΔistR inhibits cellular processes, including the expression of SOS genes. The failure in SOS gene expression does not affect the hip phenotype upon treatment with the fluoroquinolone ciprofloxacin, likely because ATP depletion avoids strong DNA damage. By contrast, Δ1-41 ΔistR cells are highly susceptible to the DNA cross-linker mitomycin C, likely because the expression of SOS-dependent repair systems is impeded. Hence, the hip phenotype of the mutant is conditional and strongly depends on the DNA-damaging agent.

Genome-Wide Identification and Expression Analysis of SOS Response Genes in Salmonella enterica Serovar Typhimurium

A bioinformatic search for LexA boxes, combined with transcriptomic detection of loci responsive to DNA damage, identified 48 members of the SOS regulon in the genome of Salmonella enterica serovar Typhimurium. Single cell analysis using fluorescent fusions revealed that heterogeneous expression is a common trait of SOS response genes, with formation of SOS^OFF and SOS^ON subpopulations. Phenotypic cell variants formed in the absence of external DNA damage show gene expression patterns that are mainly determined by the position and the heterology index of the LexA box. SOS induction upon DNA damage produces SOS^OFF and SOS^ON subpopulations that contain live and dead cells. The nature and concentration of the DNA damaging agent and the time of exposure are major factors that influence the population structure upon SOS induction. An analogy can thus be drawn between the SOS response and other bacterial stress responses that produce phenotypic cell variants.

What you see is what you get: activity-based probes in single-cell analysis of enzymatic activities

Molecular imaging methods can provide spatio-temporal information about the distribution of biomolecules or biological processes, such as certain enzymatic activities, in single cells. Within a cell, it is possible to define the subcellular location of a target, its trafficking through the cell, colocalization with other biomolecules of interest and involvement in certain cell biological processes. On the other hand, single-cell imaging promises to distinguish cells that are phenotypically different from each other. The corresponding cellular diversity comprises the presence of functionally distinct cells in a population ('phenotypic heterogeneity'), as well as dynamic cellular responses to external stimuli ('phenotypic plasticity'), which is highly relevant, e.g. during cell differentiation, activation (of immune cells), or cell death. This review focuses on applications of a certain class of chemical probes, the so-called activity-based probes (ABPs), for visualization of enzymatic activities in the single-cell context. It discusses the structure of ABPs and other chemical probes, exemplary applications of ABPs in single-cell studies in human, mouse and bacterial systems and considerations to be made with regard to data interpretation.

Microscopic Approach to Intrinsic Antibiotic Resistance

The emergence of multidrug resistance in Gram-negative pathogens is critically determined by the interplay between efflux pumps activity and low permeation outer membrane. Although phenotypic heterogeneity in isogenic cells is recognized as a key factor of treatment failure, a mathematical framework able to integrate growth dynamics and single-cell heterogeneity in antimicrobial resistance, remains absent. Here we provide such framework that bridges single-cell and colony scales in the context of bacterial survival and efficacy against drugs. Using experimental inputs, our approach produces testable outputs and reveals nontrivial collective effects with key implications for fitness and survival of the colony. This framework provides a mathematical tool to test stress response strategies in organisms that can potentially guide experiments in natural and synthetic cellular systems.

Post-transcriptional deregulation of the tisB/istR-1 toxin-antitoxin system promotes SOS-independent persister formation in Escherichia coli

Bacterial dormancy is a valuable strategy to endure unfavourable conditions. The term 'persister' has been coined for cells that tolerate antibiotic treatments due to reduced cellular activity. The type I toxin-antitoxin system tisB/istR-1 is linked to persistence in Escherichia coli, because toxin TisB depolarizes the inner membrane and causes ATP depletion. Transcription of tisB is induced upon activation of the SOS response by DNA-damaging drugs. However, translation is repressed both by a 5' structure within the tisB mRNA and by RNA antitoxin IstR-1. This tight regulation limits TisB production to SOS conditions. Deletion of both regulatory RNA elements produced a 'high persistence' mutant, which was previously assumed to depend on stochastic SOS induction and concomitant TisB production. Here, we demonstrate that the mutant generates a subpopulation of growth-retarded cells during late stationary phase, likely due to SOS-independent TisB accumulation. Cell sorting experiments revealed that the stationary phase-derived subpopulation contains most of the persister cells. Collectively our data show that deletion of the regulatory RNA elements uncouples the persister formation process from the intended stress situation and enables the formation of TisB-dependent persisters in an SOS-independent manner.

Identifying key questions in the ecology and evolution of cancer

The application of evolutionary and ecological principles to cancer prevention and treatment, as well as recognizing cancer as a selection force in nature, has gained impetus over the last 50 years. Following the initial theoretical approaches that combined knowledge from interdisciplinary fields, it became clear that using the eco-evolutionary framework is of key importance to understand cancer. We are now at a pivotal point where accumulating evidence starts to steer the future directions of the discipline and allows us to underpin the key challenges that remain to be addressed. Here, we aim to assess current advancements in the field and to suggest future directions for research. First, we summarize cancer research areas that, so far, have assimilated ecological and evolutionary principles into their approaches and illustrate their key importance. Then, we assembled 33 experts and identified 84 key questions, organized around nine major themes, to pave the foundations for research to come. We highlight the urgent need for broadening the portfolio of research directions to stimulate novel approaches at the interface of oncology and ecological and evolutionary sciences. We conclude that progressive and efficient cross-disciplinary collaborations that draw on the expertise of the fields of ecology, evolution and cancer are essential in order to efficiently address current and future questions about cancer.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

Microfluidic Single-Cell Phenotyping of the Activity of Peptide-Based Antimicrobials

Antibiotic resistance is a major challenge for modern medicine, and there is a dire need to refresh the antibiotic development pipeline to treat infections that are resistant to currently available drugs. Peptide-based antimicrobials represent a promising source of novel anti-infectives, but their development is severely impeded due to the lack of suitable techniques to accurately quantify their antimicrobial efficacy. A major problem involves the heterogeneity of cellular phenotypes in response to these peptides, even within a clonal population of bacteria. There is thus a need to develop single-cell resolution assays to quantify drug efficacy for these novel therapeutics. We present here a detailed microfluidics-microscopy protocol for testing the efficacy of peptide-based antimicrobials on hundreds to thousands of individual bacteria in well-defined microenvironments. This enables the study of cell-to-cell differences in drug response within a clonal population. It is a highly versatile tool, which can be used to quantify drug efficacy, including the number of individual survivors at defined drug doses; it even enables the potential exploration of the molecular mechanisms of action of the drug, which are often unknown in the early stages of drug development. We present here protocols for working with Escherichia coli, but organisms of different geometric shapes and sizes may also be tested with suitable modifications of the microfluidic device.

Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer

Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.

Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations

Microbial populations often experience fluctuations in nutrient complexity in their natural environment such as between high molecular weight polysaccharides and simple monosaccharides. However, it is unclear if cells can adopt growth behaviors that allow individuals to optimally respond to differences in nutrient complexity. Here, we directly control nutrient complexity and use quantitative single-cell analysis to study the growth dynamics of individuals within populations of the aquatic bacterium Caulobacter crescentus. We show that cells form clonal microcolonies when growing on the polysaccharide xylan, which is abundant in nature and degraded using extracellular cell-linked enzymes; and disperse to solitary growth modes when the corresponding monosaccharide xylose becomes available or nutrients are exhausted. We find that the cellular density required to achieve maximal growth rates is four-fold higher on xylan than on xylose, indicating that aggregating is advantageous on polysaccharides. When collectives on xylan are transitioned to xylose, cells start dispersing, indicating that colony formation is no longer beneficial and solitary behaviors might serve to reduce intercellular competition. Our study demonstrates that cells can dynamically tune their behaviors when nutrient complexity fluctuates, elucidates the quantitative advantages of distinct growth behaviors for individual cells and indicates why collective growth modes are prevalent in microbial populations.

A Coumarin-Based Analogue of Thiacetazone as Dual Covalent Inhibitor and Potential Fluorescent Label of HadA in Mycobacterium tuberculosis

A novel coumarin-based molecule, designed as a fluorescent surrogate of a thiacetazone-derived antitubercular agent, was quickly and easily synthesized from readily available starting materials. This small molecule, coined Coum-TAC, exhibited a combination of appropriate physicochemical and biological properties, including resistance toward hydrolysis and excellent antitubercular efficiency similar to that of well-known thiacetazone derivatives, as well as efficient covalent labeling of HadA, a relevant therapeutic target to combat Mycobacterium tuberculosis. More remarkably, Coum-TAC was successfully implemented as an imaging probe that is capable of labeling Mycobacterium tuberculosis in a selective manner, with an enrichment at the level of the poles, thus giving for the first time relevant insights about the polar localization of HadA in the mycobacteria.

Pulses and delays, anticipation and memory: seeing bacterial stress responses from a single-cell perspective

Stress responses are crucial for bacteria to survive harmful conditions that they encounter in the environment. Although gene regulatory mechanisms underlying stress responses in bacteria have been thoroughly characterised for decades, recent advances in imaging technologies helped to uncover previously hidden dynamics and heterogeneity that become visible at the single-cell level. Despite the diversity of stress response mechanisms, certain dynamic regulatory features are frequently seen in single cells, such as pulses, delays, stress anticipation and memory effects. Often, these dynamics are highly variable across cells. While any individual cell may not achieve an optimal stress response, phenotypic diversity can provide a benefit at the population level. In this review, we highlight microscopy studies that offer novel insights into how bacteria sense stress, regulate protective mechanisms, cope with response delays and prepare for future environmental challenges. These studies showcase developments in the single-cell imaging toolbox including gene expression reporters, FRET, super-resolution microscopy and single-molecule tracking, as well as microfluidic techniques to manipulate cells and create defined stress conditions.

Long-term iron deprivation and subsequent recovery uncover heterogeneity in the response of cyanobacterial populations

Cyanobacteria are globally important primary producers and nitrogen fixers. They are frequently limited by iron bioavailability in natural environments that often fluctuate due to rapid consumption and irregular influx of external Fe. Here we identify a succession of physiological changes in Synechocystis sp. PCC 6803 occurring over 14-16 days of iron deprivation and subsequent recovery. We observe several adaptive strategies that allow cells to push their metabolic limits under the restriction of declining intracellular Fe quotas. Interestingly, cyanobacterial populations exposed to prolonged iron deprivation showed discernible heterogeneity in cellular auto-fluorescence during the recovery process. Using FACS and microscopy techniques we revealed that only cells with high auto-fluorescence were able to grow and reconstitute thylakoid membranes. We propose that ROS-mediated damage is likely to be associated with the emergence of the two subpopulations, and, indeed, a rapid increase in intracellular ROS content was observed during the first hours following iron addition to Fe-starved cultures. These results suggest that an increasing iron supply is a double-edged sword - posing both an opportunity and a risk. Therefore, phenotypic heterogeneity within populations is crucial for the survival and proliferation of organisms facing iron fluctuations within natural environments.

Massively parallel gene expression variation measurement of a synonymous codon library

BACKGROUND

Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. While codon usage is known to affect ensemble gene expression, how codon usage influences variation in gene expression between single cells is not well understood.

RESULTS

Here, we used a Sort-seq based massively parallel strategy to quantify gene expression variation from a green fluorescent protein (GFP) library containing synonymous codons in Escherichia coli. We found that sequences containing codons with higher tRNA Adaptation Index (TAI) scores, and higher codon adaptation index (CAI) scores, have higher GFP variance. This trend is not observed for codons with high Normalized Translation Efficiency Index (nTE) scores nor from the free energy of folding of the mRNA secondary structure. GFP noise, or squared coefficient of variance (CV2), scales with mean protein abundance for low-abundant proteins but does not change at high mean protein abundance.

CONCLUSIONS

Our results suggest that the main source of noise for high-abundance proteins is likely not originating at translation elongation. Additionally, the drastic change in mean protein abundance with small changes in protein noise seen from our library implies that codon optimization can be performed without concerning gene expression noise for biotechnology applications.

Genetic and Phenotypic Heterogeneity of the Nocardiopsis alba Strains of Seawater

This study deals with the genetic and phenotypic heterogeneity of the marine Nocardiopsis alba strains isolated during pre-monsoon, monsoon and post-monsoon seasons. The isolates were characterized for their morphological and biochemical attributes, growth media preferences, antibiotic susceptibility and extracellular enzyme secretion. Nocardiopsis alba strains were assessed against 12 different antibiotics, and the responses were expressed in terms of the multiple antibiotic resistance (MAR) number. The majority of the strains produced multiple extracellular enzymes: proteases, amylases and lipases. Further, the strains were characterized on the basis of 16S rRNA gene sequencing and the majority were identified as Nocardiopsis alba along with few strains of Streptomyces lopnurensis, Nocardiopsis synnemataformans and Nocardiopsis dassonvillei. Neighbor-joining (NJ) phylogenetic tree suggested variation among the genetically similar Nocardiopsis alba species. The study establishes significant heterogeneity with respect to genetic and phenotypic characteristics of the strains of Nocardiopsis alba. Phylogenetic tree and phenogram-based comparison reflect the heterogeneity in terms of different clustering patterns of the strains. Further, the whole genome sequence data available in the literature also confirm the observed heterogeneity. Nocardiopsis alba strains displayed a relatively regressive pattern of dependence on the environmental factors based on the canonical correspondence analysis plot. The study represents cultivation, characterization, phylogenetic analysis and enzymatic potential of the Nocardiopsis alba species of seawater origin.

Effects of Tigecycline Combined with Azithromycin Against Biofilms of Multidrug-Resistant Stenotrophomonas maltophilia Isolates from a Patient in China

Purpose

Our aim was to investigate in vitro biofilm formation by S. maltophilia and the effects of antibacterial agents used to prevent biofilm formation.

Methods

Two trimethoprim/sulfamethoxazole-resistant S. maltophilia strains were isolated from the pleural effusion of a patient with cancer. The minimum inhibitory concentrations (MICs) of amikacin, azithromycin, cefoperazone/sulbactam, and tigecycline were determined. The checkerboard method was used to determine the fractional inhibitory concentration indices (FICIs). A crystal violet biofilm assay and confocal laser scanning microscopy (CLSM) were used to observe biofilm formation. In vitro effects of azithromycin combined with tigecycline on biofilms of S. maltophilia strains were tested.

Results

The two S. maltophilia isolates were confirmed to produce strong biofilms. Crystal violet biofilm assay and CLSM analysis of S. maltophilia biofilm were in the initial adhesive stage after 2 h incubation. Biofilm was in the exponential phase of growth at 12 h and reached maximal growth at 36–48 h. Compared with tigecycline or azithromycin alone, the combination of tigecycline and azithromycin increased the inhibiting effect S. maltophilia biofilm biomass after incubation for 12 h. Compared with the control group, in almost all strains treated with tigecycline and azithromycin, the biofilm was significantly suppressed significance (P<0.001). We found that 2x MIC azithromycin combined with 1x MIC tigecycline had the best inhibiting effect against the biofilm, the biofilm inhibition rates of three strains were all over 60%, the biofilm thickness was inhibited from 36.00 ± 4.00 μm to 8.00 μm, from 40.00 μm to 6.67± 2.31 μm, and from 32.00 μm to 13.33 ± 2.31 μm in SMA1, SMA2 and ATCC17666, respectively.

Conclusion

Azithromycin combined with tigecycline inhibited biofilm formation by S. maltophilia. Our study provides an experimental basis for a possible optimal treatment strategy for S. maltophilia biofilm-related infections.

Extracellular Metabolism Sets the Table for Microbial Cross-Feeding

The transfer of nutrients between cells, or cross-feeding, is a ubiquitous feature of microbial communities with emergent properties that influence our health and orchestrate global biogeochemical cycles. Cross-feeding inevitably involves the externalization of molecules. Some of these molecules directly serve as cross-fed nutrients, while others can facilitate cross-feeding. Altogether, externalized molecules that promote cross-feeding are diverse in structure, ranging from small molecules to macromolecules. The functions of these molecules are equally diverse, encompassing waste products, enzymes, toxins, signaling molecules, biofilm components, and nutrients of high value to most microbes, including the producer cell. As diverse as the externalized and transferred molecules are the cross-feeding relationships that can be derived from them. Many cross-feeding relationships can be summarized as cooperative but are also subject to exploitation. Even those relationships that appear to be cooperative exhibit some level of competition between partners. In this review, we summarize the major types of actively secreted, passively excreted, and directly transferred molecules that either form the basis of cross-feeding relationships or facilitate them. Drawing on examples from both natural and synthetic communities, we explore how the interplay between microbial physiology, environmental parameters, and the diverse functional attributes of extracellular molecules can influence cross-feeding dynamics. Though microbial cross-feeding interactions represent a burgeoning field of interest, we may have only begun to scratch the surface.

Variable inter and intraspecies alkaline phosphatase activity within single cells of revived dinoflagellates

Adaptation of cell populations to environmental changes is mediated by phenotypic variability at the single-cell level. Enzyme activity is a key factor in cell phenotype and the expression of the alkaline phosphatase activity (APA) is a fundamental phytoplankton strategy for maintaining growth under phosphate-limited conditions. Our aim was to compare the APA among cells and species revived from sediments of the Bay of Brest (Brittany, France), corresponding to a pre-eutrophication period (1940's) and a beginning of a post-eutrophication period (1990's) during which phosphate concentrations have undergone substantial variations. Both toxic marine dinoflagellate Alexandrium minutum and the non-toxic dinoflagellate Scrippsiella acuminata were revived from ancient sediments. Using microfluidics, we measured the kinetics of APA at the single-cell level. Our results indicate that all S. acuminata strains had significantly higher APA than A. minutum strains. For both species, the APA in the 1990's decade was significantly lower than in the 1940's. For the first time, our results reveal both inter and intraspecific variabilities of dinoflagellate APA and suggest that, at a half-century timescale, two different species of dinoflagellate may have undergone similar adaptative evolution to face environmental changes and acquire ecological advantages.

Temporal Patterns and Intra- and Inter-Cellular Variability in Carbon and Nitrogen Assimilation by the Unicellular Cyanobacterium Cyanothece sp. ATCC 51142

Unicellular nitrogen fixing cyanobacteria (UCYN) are abundant members of phytoplankton communities in a wide range of marine environments, including those with rapidly changing nitrogen (N) concentrations. We hypothesized that differences in N availability (N2 vs. combined N) would cause UCYN to shift strategies of intracellular N and C allocation. We used transmission electron microscopy and nanoscale secondary ion mass spectrometry imaging to track assimilation and intracellular allocation of 13C-labeled CO2 and 15N-labeled N2 or NO3 at different periods across a diel cycle in Cyanothece sp. ATCC 51142. We present new ideas on interpreting these imaging data, including the influences of pre-incubation cellular C and N contents and turnover rates of inclusion bodies. Within cultures growing diazotrophically, distinct subpopulations were detected that fixed N2 at night or in the morning. Additional significant within-population heterogeneity was likely caused by differences in the relative amounts of N assimilated into cyanophycin from sources external and internal to the cells. Whether growing on N2 or NO3, cells prioritized cyanophycin synthesis when N assimilation rates were highest. N assimilation in cells growing on NO3 switched from cyanophycin synthesis to protein synthesis, suggesting that once a cyanophycin quota is met, it is bypassed in favor of protein synthesis. Growth on NO3 also revealed that at night, there is a very low level of CO2 assimilation into polysaccharides simultaneous with their catabolism for protein synthesis. This study revealed multiple, detailed mechanisms underlying C and N management in Cyanothece that facilitate its success in dynamic aquatic environments.

PhenoGMM: Gaussian Mixture Modeling of Cytometry Data Quantifies Changes in Microbial Community Structure

Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA.

Microbial flow cytometry can rapidly characterize the status of microbial communities. Upon measurement, large amounts of quantitative single-cell data are generated, which need to be analyzed appropriately. Cytometric fingerprinting approaches are often used for this purpose. Traditional approaches either require a manual annotation of regions of interest, do not fully consider the multivariate characteristics of the data, or result in many community-describing variables. To address these shortcomings, we propose an automated model-based fingerprinting approach based on Gaussian mixture models, which we call PhenoGMM. The method successfully quantifies changes in microbial community structure based on flow cytometry data, which can be expressed in terms of cytometric diversity. We evaluate the performance of PhenoGMM using data sets from both synthetic and natural ecosystems and compare the method with a generic binning fingerprinting approach. PhenoGMM supports the rapid and quantitative screening of microbial community structure and dynamics.

IMPORTANCE Microorganisms are vital components in various ecosystems on Earth. In order to investigate the microbial diversity, researchers have largely relied on the analysis of 16S rRNA gene sequences from DNA. Flow cytometry has been proposed as an alternative technology to characterize microbial community diversity and dynamics. The technology enables a fast measurement of optical properties of individual cells. So-called fingerprinting techniques are needed in order to describe microbial community diversity and dynamics based on flow cytometry data. In this work, we propose a more advanced fingerprinting strategy based on Gaussian mixture models. We evaluated our workflow on data sets from both synthetic and natural ecosystems, illustrating its general applicability for the analysis of microbial flow cytometry data. PhenoGMM supports a rapid and quantitative analysis of microbial community structure using flow cytometry.

Bistability in oxidative stress response determines the migration behavior of phytoplankton in turbulence

Turbulence has long been known to drive phytoplankton fitness and species succession: motile species dominate in calmer environments and non-motile species in turbulent conditions. Yet a mechanistic understanding of the effect of turbulence on phytoplankton migratory behavior and physiology is lacking. By combining a method to generate turbulent cues, quantification of stress accumulation and physiology, and a mathematical model of stress dynamics, we show that motile phytoplankton use their mechanical stability to sense the intensity of turbulent cues and integrate these cues in time via stress signaling to trigger switches in migratory behavior. The stress-mediated warning strategy we discovered provides a paradigm for how phytoplankton cope with turbulence, thereby potentially governing which species will be successful in a changing ocean.

Turbulence is an important determinant of phytoplankton physiology, often leading to cell stress and damage. Turbulence affects phytoplankton migration both by transporting cells and by triggering switches in migratory behavior, whereby vertically migrating cells can actively invert their direction of migration upon exposure to turbulent cues. However, a mechanistic link between single-cell physiology and vertical migration of phytoplankton in turbulence is currently missing. Here, by combining physiological and behavioral experiments with a mathematical model of stress accumulation and dissipation, we show that the mechanism responsible for the switch in the direction of migration in the marine raphidophyte Heterosigma akashiwo is the integration of reactive oxygen species (ROS) signaling generated by turbulent cues. Within timescales as short as tens of seconds, the emergent downward-migrating subpopulation exhibited a twofold increase in ROS, an indicator of stress, 15% lower photosynthetic efficiency, and 35% lower growth rate over multiple generations compared to the upward-migrating subpopulation. The origin of the behavioral split as a result of a bistable oxidative stress response is corroborated by the observation that exposure of cells to exogenous stressors (H₂O₂, UV-A radiation, or high irradiance), in lieu of turbulence, caused comparable ROS accumulation and an equivalent split into the two subpopulations. By providing a mechanistic link between the single-cell mechanics of swimming and physiology on the one side and the emergent population-scale migratory response and impact on fitness on the other, the ROS-mediated early warning response we discovered contributes to our understanding of phytoplankton community composition in future ocean conditions.

The impact of mistranslation on phenotypic variability and fitness

Phenotypic variation is widespread in natural populations, and can significantly alter population ecology and evolution. Phenotypic variation often reflects underlying genetic variation, but also manifests via non-heritable mechanisms. For instance, translation errors result in about 10% of cellular proteins carrying altered sequences. Thus, proteome diversification arising from translation errors can potentially generate phenotypic variability, in turn increasing variability in the fate of cells or of populations. However, the link between protein diversity and phenotypic variability remains unverified. We manipulated mistranslation levels in Escherichia coli, and measured phenotypic variability between single cells (individual-level variation), as well as replicate populations (population-level variation). Monitoring growth and survival, we find that mistranslation indeed increases variation across E. coli cells, but does not consistently increase variability in growth parameters across replicate populations. Interestingly, although any deviation from the wild-type (WT) level of mistranslation reduces fitness in an optimal environment, the increased variation is associated with a survival benefit under stress. Hence, we suggest that mistranslation-induced phenotypic variation can impact growth and survival and has the potential to alter evolutionary trajectories.

Experimentally-validated correlation analysis reveals new anaerobic methane oxidation partnerships with consortium-level heterogeneity in diazotrophy

Archaeal anaerobic methanotrophs ("ANME") and sulfate-reducing Deltaproteobacteria ("SRB") form symbiotic multicellular consortia capable of anaerobic methane oxidation (AOM), and in so doing modulate methane flux from marine sediments. The specificity with which ANME associate with particular SRB partners in situ, however, is poorly understood. To characterize partnership specificity in ANME-SRB consortia, we applied the correlation inference technique SparCC to 310 16S rRNA amplicon libraries prepared from Costa Rica seep sediment samples, uncovering a strong positive correlation between ANME-2b and members of a clade of Deltaproteobacteria we termed SEEP-SRB1g. We confirmed this association by examining 16S rRNA diversity in individual ANME-SRB consortia sorted using flow cytometry and by imaging ANME-SRB consortia with fluorescence in situ hybridization (FISH) microscopy using newly-designed probes targeting the SEEP-SRB1g clade. Analysis of genome bins belonging to SEEP-SRB1g revealed the presence of a complete nifHDK operon required for diazotrophy, unusual in published genomes of ANME-associated SRB. Active expression of nifH in SEEP-SRB1g within ANME-2b-SEEP-SRB1g consortia was then demonstrated by microscopy using hybridization chain reaction (HCR-) FISH targeting nifH transcripts and diazotrophic activity was documented by FISH-nanoSIMS experiments. NanoSIMS analysis of ANME-2b-SEEP-SRB1g consortia incubated with a headspace containing CH4 and 15N2 revealed differences in cellular 15N-enrichment between the two partners that varied between individual consortia, with SEEP-SRB1g cells enriched in 15N relative to ANME-2b in one consortium and the opposite pattern observed in others, indicating both ANME-2b and SEEP-SRB1g are capable of nitrogen fixation, but with consortium-specific variation in whether the archaea or bacterial partner is the dominant diazotroph.

Non-genetic inheritance restraint of cell-to-cell variation

Heterogeneity in physical and functional characteristics of cells (e.g. size, cycle time, growth rate, protein concentration) proliferates within an isogenic population due to stochasticity in intracellular biochemical processes and in the distribution of resources during divisions. Conversely, it is limited in part by the inheritance of cellular components between consecutive generations. Here we introduce a new experimental method for measuring proliferation of heterogeneity in bacterial cell characteristics, based on measuring how two sister cells become different from each other over time. Our measurements provide the inheritance dynamics of different cellular properties, and the 'inertia' of cells to maintain these properties along time. We find that inheritance dynamics are property specific and can exhibit long-term memory (∼10 generations) that works to restrain variation among cells. Our results can reveal mechanisms of non-genetic inheritance in bacteria and help understand how cells control their properties and heterogeneity within isogenic cell populations.

Insights on the Control of Yeast Single-Cell Growth Variability by Members of the Trehalose Phosphate Synthase (TPS) Complex

Single-cell variability of growth is a biological phenomenon that has attracted growing interest in recent years. Important progress has been made in the knowledge of the origin of cell-to-cell heterogeneity of growth, especially in microbial cells. To better understand the origins of such heterogeneity at the single-cell level, we developed a new methodological pipeline that coupled cytometry-based cell sorting with automatized microscopy and image analysis to score the growth rate of thousands of single cells. This allowed investigating the influence of the initial amount of proteins of interest on the subsequent growth of the microcolony. As a preliminary step to validate this experimental setup, we referred to previous findings in yeast where the expression level of Tsl1, a member of the Trehalose Phosphate Synthase (TPS) complex, negatively correlated with cell division rate. We unfortunately could not find any influence of the initial TSL1 expression level on the growth rate of the microcolonies. We also analyzed the effect of the natural variations of trehalose-6-phosphate synthase (TPS1) expression on cell-to-cell growth heterogeneity, but we did not find any correlation. However, due to the already known altered growth of the tps1Δ mutants, we tested this strain at the single-cell level on a permissive carbon source. This mutant showed an outstanding lack of reproducibility of growth rate distributions as compared to the wild-type strain, with variable proportions of non-growing cells between cultivations and more heterogeneous microcolonies in terms of individual growth rates. Interestingly, this variable behavior at the single-cell level was reminiscent to the high variability that is also stochastically suffered at the population level when cultivating this tps1Δ strain, even when using controlled bioreactors.

Cooperative metabolic resource allocation in spatially-structured systems

Natural selection has shaped the evolution of cells and multi-cellular organisms such that social cooperation can often be preferred over an individualistic approach to metabolic regulation. This paper extends a framework for dynamic metabolic resource allocation based on the maximum entropy principle to spatiotemporal models of metabolism with cooperation. Much like the maximum entropy principle encapsulates 'bet-hedging' behaviour displayed by organisms dealing with future uncertainty in a fluctuating environment, its cooperative extension describes how individuals adapt their metabolic resource allocation strategy to further accommodate limited knowledge about the welfare of others within a community. The resulting theory explains why local regulation of metabolic cross-feeding can fulfil a community-wide metabolic objective if individuals take into consideration an ensemble measure of total population performance as the only form of global information. The latter is likely supplied by quorum sensing in microbial systems or signalling molecules such as hormones in multi-cellular eukaryotic organisms.

Analysis of Pseudomonas aeruginosa c-di-GMP High and Low Subpopulations Using Flow-assisted Cell Sorting (FACS) and Quantitative Reverse Transcriptase PCR (qRT-PCR)

Cyclic diguanylate monophosphate (c-di-GMP) is a second messenger signaling molecule that drives the transition from planktonic to the biofilm mode of growth in many bacterial species. Pseudomonas aeruginosa has at least two surface sensing systems that produce c-di-GMP in response to surface attachment, the Wsp and Pil-Chp systems. We recently used a plasmid-based c-di-GMP reporter (pP _cdrA::gfp ) to describe how the Wsp system generates heterogeneity in surface sensing, resulting in two physiologically distinct subpopulations of cells during early biofilm formation. One subpopulation has elevated c-di-GMP and produces biofilm matrix, serving as the founders of initial microcolonies. The other subpopulation has low c-di-GMP and engages in surface motility, allowing for exploration of the surface. Here, we describe the protocol for a key experiment to confirm our initial observation of c-di-GMP heterogeneity during surface sensing: the use of flow-assisted cell sorting (FACS) to isolate subpopulations of cells with high and low c-di-GMP reporter activity, followed by quantitative Reverse Transcriptase PCR (qRT-PCR) of genes that are known to be transcriptionally regulated in response to cellular c-di-GMP levels (pelA, pslA). This protocol can be adapted by others to isolate subpopulations of high- and low- c-di-GMP P. aeruginosa cells that are genetically identical, but phenotypically distinct for future experiments examining specific mRNA transcripts as we did or, presumably, for additional applications like RNAseq, proteomics, or TNseq. Graphical abstract.

RESTAMP - Rate estimates by sequence-tag analysis of microbial populations

Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and antibiotic action. Several methods based on marker-loss or few inheritable neutral markers exist that allow estimating microbial division and death rates, each of which has advantages and limitations. Technical bottlenecks, i.e., experimental sampling events, during the experiment can distort the rate estimates and are typically unaccounted for or require additional calibration experiments. In this work, we introduce RESTAMP (Rate Estimates by Sequence Tag Analysis of Microbial Populations) as a method for determining bacterial division and death rates. This method uses hundreds of fitness neutral sequence barcodes to measure the rates and account for experimental bottlenecks at the same time. We experimentally validate RESTAMP and compare it to established plasmid loss methods. We find that RESTAMP has a number of advantages over plasmid loss or previous marker based techniques. (i) It enables to correct the distortion of rate estimates by technical bottlenecks. (ii) Rate estimates are independent of the sequence tag distribution in the starting culture allowing the use of an arbitrary number of tags. (iii) It introduces a bottleneck sensitivity measure that can be used to maximize the accuracy of the experiment. RESTAMP allows studying microbial population dynamics with great resolution over a wide dynamic range and can thus advance our understanding of host-pathogen interactions or the mechanisms of antibiotic action.

Persistence of Intracellular Bacterial Pathogens-With a Focus on the Metabolic Perspective

Persistence has evolved as a potent survival strategy to overcome adverse environmental conditions. This capability is common to almost all bacteria, including all human bacterial pathogens and likely connected to chronic infections caused by some of these pathogens. Although the majority of a bacterial cell population will be killed by the particular stressors, like antibiotics, oxygen and nitrogen radicals, nutrient starvation and others, a varying subpopulation (termed persisters) will withstand the stress situation and will be able to revive once the stress is removed. Several factors and pathways have been identified in the past that apparently favor the formation of persistence, such as various toxin/antitoxin modules or stringent response together with the alarmone (p)ppGpp. However, persistence can occur stochastically in few cells even of stress-free bacterial populations. Growth of these cells could then be induced by the stress conditions. In this review, we focus on the persister formation of human intracellular bacterial pathogens, some of which belong to the most successful persister producers but lack some or even all of the assumed persistence-triggering factors and pathways. We propose a mechanism for the persister formation of these bacterial pathogens which is based on their specific intracellular bipartite metabolism. We postulate that this mode of metabolism ultimately leads, under certain starvation conditions, to the stalling of DNA replication initiation which may be causative for the persister state.