Colony-live--a high-throughput method for measuring microbial colony growth kinetics--reveals diverse growth effects of gene knockouts in Escherichia coli

Nonlethal deleterious mutation-induced stress accelerates bacterial aging

Random mutagenesis, including when it leads to loss of gene function, is a key mechanism enabling microorganisms' long-term adaptation to new environments. However, loss-of-function mutations are often deleterious, triggering, in turn, cellular stress and complex homeostatic stress responses, called "allostasis," to promote cell survival. Here, we characterize the differential impacts of 65 nonlethal, deleterious single-gene deletions on Escherichia coli growth in three different growth environments. Further assessments of select mutants, namely, those bearing single adenosine triphosphate (ATP) synthase subunit deletions, reveal that mutants display reorganized transcriptome profiles that reflect both the environment and the specific gene deletion. We also find that ATP synthase α-subunit deleted (ΔatpA) cells exhibit elevated metabolic rates while having slower growth compared to wild-type (wt) E. coli cells. At the single-cell level, compared to wt cells, individual ΔatpA cells display near normal proliferation profiles but enter a postreplicative state earlier and exhibit a distinct senescence phenotype. These results highlight the complex interplay between genomic diversity, adaptation, and stress response and uncover an "aging cost" to individual bacterial cells for maintaining population-level resilience to environmental and genetic stress; they also suggest potential bacteriostatic antibiotic targets and -as select human genetic diseases display highly similar phenotypes, - a bacterial origin of some human diseases.

Sm-like protein Rof inhibits transcription termination factor ρ by binding site obstruction and conformational insulation

Transcription termination factor ρ is a hexameric, RNA-dependent NTPase that can adopt active closed-ring and inactive open-ring conformations. The Sm-like protein Rof, a homolog of the RNA chaperone Hfq, inhibits ρ-dependent termination in vivo but recapitulation of this activity in vitro has proven difficult and the precise mode of Rof action is presently unknown. Here, our cryo-EM structures of ρ-Rof and ρ-RNA complexes show that Rof undergoes pronounced conformational changes to bind ρ at the protomer interfaces, undercutting ρ conformational dynamics associated with ring closure and occluding extended primary RNA-binding sites that are also part of interfaces between ρ and RNA polymerase. Consistently, Rof impedes ρ ring closure, ρ-RNA interactions and ρ association with transcription elongation complexes. Structure-guided mutagenesis coupled with functional assays confirms that the observed ρ-Rof interface is required for Rof-mediated inhibition of cell growth and ρ-termination in vitro. Bioinformatic analyses reveal that Rof is restricted to Pseudomonadota and that the ρ-Rof interface is conserved. Genomic contexts of rof differ between Enterobacteriaceae and Vibrionaceae, suggesting distinct modes of Rof regulation. We hypothesize that Rof and other cellular anti-terminators silence ρ under diverse, but yet to be identified, stress conditions when unrestrained transcription termination by ρ may be detrimental.

High-Throughput Screening Method Using Escherichia coli Keio Mutants for Assessing Primary Damage Mechanism of Antimicrobials

The Escherichia coli Keio mutant collection has been a tool for assessing the role of specific genes and determining their role in E. coli physiology and uncovering novel functions. In this work, specific mutants in the DNA repair pathways and oxidative stress response were evaluated to identify the primary targets of silver nanoparticles (NPs) and their mechanism of action. The results presented in this work suggest that NPs mainly target DNA via double-strand breaks and base modifications since the recA, uvrC, mutL, and nfo mutants rendered the most susceptible phenotype, rather than involving the oxidative stress response. Concomitantly, during the establishment of the control conditions for each mutant, the katG and sodA mutants showed a hypersensitive phenotype to mitomycin C, an alkylating agent. Thus, we propose that KatG catalase plays a key role as a cellular chaperone, as reported previously for the filamentous fungus Neurospora crassa, a large subunit catalase. The Keio collection mutants may also be a key tool for assessing the resistance mechanism to metallic NPs by using their potential to identify novel pathways involved in the resistance to NPs.

Anaerobic glucose uptake in Pseudomonas putida KT2440 in a bioelectrochemical system

Providing an anodic potential in a bio-electrochemical system to the obligate aerobe Pseudomonas putida enables anaerobic survival and allows the cells to overcome redox imbalances. In this setup, the bacteria could be exploited to produce chemicals via oxidative pathways at high yield. However, the absence of anaerobic growth and low carbon turnover rates remain as obstacles for the application of such an electro-fermentation technology. Growth and carbon turnover start with carbon uptake into the periplasm and cytosol. P. putida KT2440 has three native transporting systems for glucose, each differing in energy and redox demand. This architecture previously led to the hypothesis that internal redox and energy constraints ultimately limit cytoplasmic carbon utilization in a bio-electrochemical system. However, it remains largely unclear which uptake route is predominantly used by P. putida under electro-fermentative conditions. To elucidate this, we created three gene deletion mutants of P. putida KT2440, forcing the cells to exclusively utilize one of the routes. When grown in a bio-electrochemical system, the pathway mutants were heavily affected in terms of sugar consumption, current output and product formation. Surprisingly, however, we found that about half of the acetate formed in the cytoplasm originated from carbon that was put into the system via the inoculation biomass, while the other half came from the consumption of substrate. The deletion of individual sugar uptake routes did not alter significantly the secreted acetate concentrations among different strains even with different carbon sources. This means that the stoichiometry of the sugar uptake routes is not a limiting factor during electro-fermentation and that the low rates might be caused by other reasons, for example energy limitations or a yet-to-be-identified oxygen-dependent regulatory mechanism.

Sm-like protein Rof inhibits transcription termination factor ρ by binding site obstruction and conformational insulation

Transcription termination factor ρ is a hexameric, RNA-dependent NTPase that can adopt active closed-ring and inactive open-ring conformations. The Sm-like protein Rof, a homolog of the RNA chaperone Hfq, inhibits ρ-dependent termination in vivo but recapitulation of this activity in vitro has proven difficult and the precise mode of Rof action is presently unknown. Our electron microscopic structures of ρ-Rof and ρ-RNA complexes show that Rof undergoes pronounced conformational changes to bind ρ at the protomer interfaces, undercutting ρ conformational dynamics associated with ring closure and occluding extended primary RNA-binding sites that are also part of interfaces between ρ and RNA polymerase. Consistently, Rof impedes ρ ring closure, ρ-RNA interactions, and ρ association with transcription elongation complexes. Structure-guided mutagenesis coupled with functional assays confirmed that the observed ρ-Rof interface is required for Rof-mediated inhibition of cell growth and ρ-termination in vitro. Bioinformatic analyses revealed that Rof is restricted to Pseudomonadota and that the ρ-Rof interface is conserved. Genomic contexts of rof differ between Enterobacteriaceae and Vibrionaceae, suggesting distinct modes of Rof regulation. We hypothesize that Rof and other cellular anti-terminators silence ρ under diverse, but yet to be identified, stress conditions when unrestrained transcription termination by ρ would be lethal.

Optimal density of bacterial cells

A substantial fraction of the bacterial cytosol is occupied by catalysts and their substrates. While a higher volume density of catalysts and substrates might boost biochemical fluxes, the resulting molecular crowding can slow down diffusion, perturb the reactions' Gibbs free energies, and reduce the catalytic efficiency of proteins. Due to these tradeoffs, dry mass density likely possesses an optimum that facilitates maximal cellular growth and that is interdependent on the cytosolic molecule size distribution. Here, we analyze the balanced growth of a model cell, accounting systematically for crowding effects on reaction kinetics. Its optimal cytosolic volume occupancy depends on the nutrient-dependent resource allocation into large ribosomal vs. small metabolic macromolecules, reflecting a tradeoff between the saturation of metabolic enzymes, favoring larger occupancies with higher encounter rates, and the inhibition of the ribosomes, favoring lower occupancies with unhindered diffusion of tRNAs. Our predictions across growth rates are quantitatively consistent with the experimentally observed reduction in volume occupancy on rich media compared to minimal media in E. coli. Strong deviations from optimal cytosolic occupancy only lead to minute reductions in growth rate, which are nevertheless evolutionarily relevant due to large bacterial population sizes. In sum, cytosolic density variation in bacterial cells appears to be consistent with an optimality principle of cellular efficiency.

Quantitative approaches to study phenotypic effects of large-scale genetic perturbations

How microbes interact with their environment and how the complex interplay of their genes enables them to survive and thrive under stress is a fundamental question in microbial system biology, which is also important from a public health perspective. Large-scale studies of gene-gene, gene-drug, and drug-drug interactions have proven to be powerful tools for elucidating gene function and functional modules in the cell. Approaches that systematically quantify phenotypes in libraries of microbial strains with genome-wide genetic perturbations are crucial for progress in this area. Here, we review recent advances in this field, and point out applications to the study of gene-drug interactions. We highlight newly developed techniques for the rapid generation of genome-wide mutant libraries and the high-throughput measurement of more complex phenotypes and other observables, such as cell morphology or thermal stability of the proteome.

Use of the speckle imaging sub-pixel correlation analysis in revealing a mechanism of microbial colony growth

The microbial colony growth is driven by the activity of the cells located on the edges of the colony. However, this process is not visible unless specific staining or cross-sectioning of the colony is done. Speckle imaging technology is a non-invasive method that allows visualization of the zones of increased microbial activity within the colony. In this study, the laser speckle imaging technique was used to record the growth of the microbial colonies. This method was tested on three different microorganisms: Vibrio natriegens, Escherichia coli, and Staphylococcus aureus. The results showed that the speckle analysis system is not only able to record the growth of the microbial colony but also to visualize the microbial growth activity in different parts of the colony. The developed speckle imaging technique visualizes the zone of "the highest microbial activity" migrating from the center to the periphery of the colony. The results confirm the accuracy of the previous models of colony growth and provide algorithms for analysis of microbial activity within the colony.

Automation of yeast spot assays using an affordable liquid handling robot

The spot assay of the budding yeast Saccharomyces cerevisiae is an experimental method that is used to evaluate the effect of genotypes, medium conditions, and environmental stresses on cell growth and survival. Automation of the spot assay experiments from preparing a dilution series to spotting to observing spots continuously has been implemented based on large laboratory automation devices and robots, especially for high-throughput functional screening assays. However, there has yet to be an affordable solution for the automated spot assays suited to researchers in average laboratories and with high customizability for end-users. To make reproducible spot assay experiments widely available, we have automated the plate-based yeast spot assay of budding yeast using Opentrons OT-2 (OT-2), an affordable liquid-handling robot, and a flatbed scanner. We prepared a 3D-printed mount for the Petri dish to allow for precise placement of the Petri dish inside the OT-2. To account for the uneven height of the agar plates, which were made by human hands, we devised a method to adjust the z-position of the pipette tips based on the weight of each agar plate. During the incubation of the agar plates, a flatbed scanner was used to automatically take images of the agar plates over time, allowing researchers to quantify and compare the cell density within the spots at optimal time points a posteriori. Furthermore, the accuracy of the newly developed automated spot assay was verified by performing spot assays with human experimenters and the OT-2 and quantifying the yeast-grown area of the spots. This study will contribute to the introduction of automated spot assays and the automated acquisition of growth processes in conventional laboratories that are not adapted for high-throughput laboratory automation.

Analysis of a Library of Escherichia coli Transporter Knockout Strains to Identify Transport Pathways of Antibiotics

Antibiotic resistance is a major global healthcare issue. Antibiotic compounds cross the bacterial cell membrane via membrane transporters, and a major mechanism of antibiotic resistance is through modification of the membrane transporters to increase the efflux or reduce the influx of antibiotics. Targeting these transporters is a potential avenue to combat antibiotic resistance. In this study, we used an automated screening pipeline to evaluate the growth of a library of 447 Escherichia coli transporter knockout strains exposed to sub-inhibitory concentrations of 18 diverse antimicrobials. We found numerous knockout strains that showed more resistant or sensitive phenotypes to specific antimicrobials, suggestive of transport pathways. We highlight several specific drug-transporter interactions that we identified and provide the full dataset, which will be a useful resource in further research on antimicrobial transport pathways. Overall, we determined that transporters are involved in modulating the efficacy of almost all the antimicrobial compounds tested and can, thus, play a major role in the development of antimicrobial resistance.

Methods to monitor bacterial growth and replicative rates at the single-cell level

The heterogeneity of bacterial growth and replicative rates within a population was proposed a century ago notably to explain the presence of bacterial persisters. The term "growth rate" at the single-cell level corresponds to the increase in size or mass of an individual bacterium while the "replicative rate" refers to its division capacity within a defined temporality. After a decades long hiatus, recent technical innovative approaches allow population growth and replicative rates heterogeneity monitoring at the single-cell level resuming in earnest. Among these techniques, the oldest and widely used is time-lapse microscopy, most recently combined with microfluidics. We also discuss recent fluorescence dilution methods informing only on replicative rates and best suited. Some new elegant single cell methods so far only sporadically used such as buoyant mass measurement and stable isotope probing have emerged. Overall, such tools are widely used to investigate and compare the growth and replicative rates of bacteria displaying drug-persistent behaviors to that of bacteria growing in specific ecological niches or collected from patients. In this review, we describe the current methods available, discussing both the type of queries these have been used to answer and the specific strengths and limitations of each method.

High-Throughput, High-Precision Colony Phenotyping with Pyphe

Colony fitness screens are powerful approaches for functional genomics and genetics. This protocol describes experimental and computational procedures for assaying the fitness of thousands of microbial strains in numerous conditions in parallel. Data analysis is based on pyphe, an all-in-one bioinformatics toolbox for scanning, image analysis, data normalization, and interpretation. We describe a standard protocol where endpoint colony areas are used as fitness proxy and two variations on this, one using colony growth curves and one using colony viability staining with phloxine B. Different strategies for experimental design, normalization and quality control are discussed. Using these approaches, it is possible to collect hundreds of thousands of data points, with low technical noise levels around 5%, in an experiment typically lasting 2 weeks or less.

Morphological and Transcriptional Responses to CRISPRi Knockdown of Essential Genes in Escherichia coli

CRISPR interference (CRISPRi) has facilitated the study of essential genes in diverse organisms using both high-throughput and targeted approaches. Despite the promise of this technique, no comprehensive arrayed CRISPRi library targeting essential genes exists for the model bacterium Escherichia coli, or for any Gram-negative species. Here, we built and characterized such a library. Each of the ∼500 strains in our E. coli library contains an inducible, chromosomally integrated single guide RNA (sgRNA) targeting an essential (or selected nonessential) gene and can be mated with a pseudo-Hfr donor strain carrying a dcas9 cassette to create a CRISPRi knockdown strain. Using this system, we built an arrayed library of CRISPRi strains and performed population and single-cell growth and morphology measurements as well as targeted follow-up experiments. These studies found that inhibiting translation causes an extended lag phase, identified new modulators of cell morphology, and revealed that the morphogene mreB is subject to transcriptional feedback regulation, which is critical for the maintenance of morphology. Our findings highlight canonical and noncanonical roles for essential genes in numerous aspects of cellular homeostasis. IMPORTANCE Essential genes make up only ∼5 to 10% of the genetic complement in most organisms but occupy much of their protein synthesis and account for almost all antibiotic targets. Despite the importance of essential genes, their intractability has, until recently, hampered efforts to study them. CRISPRi has facilitated the study of essential genes by allowing inducible and titratable depletion. However, all large-scale CRISPRi studies in Gram-negative bacteria thus far have used plasmids to express CRISPRi components and have been constructed in pools, limiting their utility for targeted assays and complicating the determination of antibiotic effects. Here, we use a modular method to construct an arrayed library of chromosomally integrated CRISPRi strains targeting the essential genes of the model bacterium Escherichia coli. This library enables targeted studies of essential gene depletions and high-throughput determination of antibiotic targets and facilitates studies targeting the outer membrane, an essential component that serves as the major barrier to antibiotics.

Quantifying Variation in Bacterial Reproductive Fitness: a High-Throughput Method

Reproductive fitness of bacteria is a major factor in the evolution and persistence of antimicrobial resistance and may play an important role as a pathogen factor in severe infections. With a computational approach to quantify fitness in bacteria growing competitively on agar plates, our high-throughput method has been designed to obtain additional phenotypic data for antimicrobial resistance analysis at a low cost.

To evaluate changes in reproductive fitness of bacteria, e.g., after acquisition of antimicrobial resistance, a low-cost high-throughput method to analyze bacterial growth on agar is desirable for broad usability. In our bacterial quantitative fitness analysis (BaQFA), arrayed cultures are spotted on agar and photographed sequentially while growing. These time-lapse images are analyzed using a purpose-built open-source software to derive normalized image intensity (NI) values for each culture spot. Subsequently, a Gompertz growth model is fitted to NI values, and fitness is calculated from model parameters. To represent a range of clinically important pathogenic bacteria, we used different strains of Enterococcus faecium, Escherichia coli, and Staphylococcus aureus, with and without antimicrobial resistance. Relative competitive fitness (RCF) was defined as the mean fitness ratio of two strains growing competitively on one plate.BaQFA permitted the accurate construction of growth curves from bacteria grown on semisolid agar plates and fitting of Gompertz models. Normalized image intensity values showed a strong association with the total CFU/ml count per spotted culture (P < 0.001) for all strains of the three species. BaQFA showed relevant reproductive fitness differences between individual strains, suggesting substantially higher fitness of methicillin-resistant S. aureus JE2 than Cowan (RCF, 1.58; P < 0.001). Similarly, the vancomycin-resistant E. faecium ST172b showed higher competitive fitness than susceptible E. faecium ST172 (RCF, 1.59; P < 0.001). Our BaQFA method allows detection of fitness differences between bacterial strains and may help to estimate epidemiological antimicrobial persistence or contribute to the prediction of clinical outcomes in severe infections.

IMPORTANCE Reproductive fitness of bacteria is a major factor in the evolution and persistence of antimicrobial resistance and may play an important role in severe infections. With a computational approach to quantify fitness in bacteria growing competitively on agar plates, our high-throughput method has been designed to obtain additional phenotypic data for antimicrobial resistance analysis at a low cost. Furthermore, our bacterial quantitative fitness analysis (BaQFA) enables the investigation of a link between bacterial fitness and clinical outcomes in severe invasive bacterial infections. This may allow future use of our method for patient management and risk stratification of clinical outcomes. Our proposed method uses open-source software and a hardware setup that can utilize consumer electronics. This will enable a wider community of researchers, including those from low-resource countries, where the burden of antimicrobial resistance is highest, to obtain valuable information about emerging bacterial strains.

Involvement of glycogen metabolism in circadian control of UV resistance in cyanobacteria

Most organisms harbor circadian clocks as endogenous timing systems in order to adapt to daily environmental changes, such as exposure to ultraviolet (UV) light. It has been hypothesized that the circadian clock evolved to prevent UV-sensitive activities, such as DNA replication and cell division, during the daytime. Indeed, circadian control of UV resistance has been reported in several eukaryotic organisms, from algae to higher organisms, although the underlying mechanisms remain unknown. Here, we demonstrate that the unicellular cyanobacterium Synechococcus elongatus PCC 7942 exhibits a circadian rhythm in resistance to UV-C and UV-B light, which is higher during subjective dawn and lower during subjective dusk. Nullification of the clock gene cluster kaiABC or the DNA-photolyase phr abolished rhythmicity with constitutively lower resistance to UV-C light, and amino acid substitutions of KaiC altered the period lengths of the UV-C resistance rhythm. In order to elucidate the molecular mechanism underlying the circadian regulation of UV-C resistance, transposon insertion mutants that alter UV-C resistance were isolated. Mutations to the master circadian output mediator genes sasA and rpaA and the glycogen degradation enzyme gene glgP abolished circadian rhythms of UV-C resistance with constitutively high UV-C resistance. Combining these results with further experiments using ATP synthesis inhibitor and strains with modified metabolic pathways, we showed that UV-C resistance is weakened by directing more metabolic flux from the glycogen degradation to catabolic pathway such as oxidative pentose phosphate pathway and glycolysis. We suggest glycogen-related metabolism in the dark affects circadian control in UV sensitivity, while the light masks this effect through the photolyase function.

Most organisms harbor circadian clocks to adapt to daily environmental changes. It has been hypothesized that adaptation to UV radiation during the day was a driving force of the evolution of the circadian clock (known as “the flight from light” hypothesis). Thus, understanding the relationship with UV resistance is important to consider the physiological relevance and an evolutionary origin of the circadian clock. We here demonstrate that the unicellular cyanobacterium, Synechococcus elongatus exhibits a circadian rhythm in resistance to UV-C light, which is higher and lower during subjective dawn and dusk, respectively. This rhythm was abolished by nullification of the clock gene cluster kaiABC, and the period length was changed consistently by period mutations on kaiC. Genetic screening revealed that nullification of clock-associating genes sasA, cikA and rpaA, and of a glycogen degradation enzyme gene glgP abolished or attenuated the UV-resistance rhythm. Combining these results with further experiments using an ATP synthesis inhibitor and strains with modified metabolic pathways, we suggest a that the circadian clock confers adaptive fitness by balancing a trade-off between glycogen-related energy metabolism and the UV-resistance property.

Gene Dispensability in Escherichia coli Grown in Thirty Different Carbon Environments

While there has been much study of bacterial gene dispensability, there is a lack of comprehensive genome-scale examinations of the impact of gene deletion on growth in different carbon sources. In this context, a lot can be learned from such experiments in the model microbe Escherichia coli where much is already understood and there are existing tools for the investigation of carbon metabolism and physiology (1). Gene deletion studies have practical potential in the field of antibiotic drug discovery where there is emerging interest in bacterial central metabolism as a target for new antibiotics (2). Furthermore, some carbon utilization pathways have been shown to be critical for initiating and maintaining infection for certain pathogens and sites of infection (3–5). Here, with the use of high-throughput solid medium phenotyping methods, we have generated kinetic growth measurements for 3,796 genes under 30 different carbon source conditions. This data set provides a foundation for research that will improve our understanding of genes with unknown function, aid in predicting potential antibiotic targets, validate and advance metabolic models, and help to develop our understanding of E. coli metabolism.

Central metabolism is a topic that has been studied for decades, and yet, this process is still not fully understood in Escherichia coli, perhaps the most amenable and well-studied model organism in biology. To further our understanding, we used a high-throughput method to measure the growth kinetics of each of 3,796 E. coli single-gene deletion mutants in 30 different carbon sources. In total, there were 342 genes (9.01%) encompassing a breadth of biological functions that showed a growth phenotype on at least 1 carbon source, demonstrating that carbon metabolism is closely linked to a large number of processes in the cell. We identified 74 genes that showed low growth in 90% of conditions, defining a set of genes which are essential in nutrient-limited media, regardless of the carbon source. The data are compiled into a Web application, Carbon Phenotype Explorer (CarPE), to facilitate easy visualization of growth curves for each mutant strain in each carbon source. Our experimental data matched closely with the predictions from the EcoCyc metabolic model which uses flux balance analysis to predict growth phenotypes. From our comparisons to the model, we found that, unexpectedly, phosphoenolpyruvate carboxylase (ppc) was required for robust growth in most carbon sources other than most trichloroacetic acid (TCA) cycle intermediates. We also identified 51 poorly annotated genes that showed a low growth phenotype in at least 1 carbon source, which allowed us to form hypotheses about the functions of these genes. From this list, we further characterized the ydhC gene and demonstrated its role in adenosine efflux.

Correlated chromosomal periodicities according to the growth rate and gene expression

Linking genetic information to population fitness is crucial to understanding living organisms. Despite the abundant knowledge of the genetic contribution to growth, the overall patterns/features connecting genes, their expression, and growth remain unclear. To reveal the quantitative and direct connections, systematic growth assays of single-gene knockout Escherichia coli strains under both rich and poor nutritional conditions were performed; subsequently, the resultant growth rates were associated with the original expression levels of the knockout genes in the parental genome. Comparative analysis of growth and the transcriptome identified not only the nutritionally differentiated fitness cost genes but also a significant correlation between the growth rates of the single-gene knockout strains and the original expression levels of these knockout genes in the parental strain, regardless of the nutritional variation. In addition, the coordinated chromosomal periodicities of the wild-type transcriptome and the growth rates of the strains lacking the corresponding genes were observed. The common six-period periodicity was somehow attributed to the essential genes, although the underlying mechanism remains to be addressed. The correlated chromosomal periodicities associated with the gene expression-growth dataset were highly valuable for bacterial growth prediction and discovering the working principles governing minimal genetic information.

Pyphe, a python toolbox for assessing microbial growth and cell viability in high-throughput colony screens

Microbial fitness screens are a key technique in functional genomics. We present an all-in-one solution, pyphe, for automating and improving data analysis pipelines associated with large-scale fitness screens, including image acquisition and quantification, data normalisation, and statistical analysis. Pyphe is versatile and processes fitness data from colony sizes, viability scores from phloxine B staining or colony growth curves, all obtained with inexpensive transilluminating flatbed scanners. We apply pyphe to show that the fitness information contained in late endpoint measurements of colony sizes is similar to maximum growth slopes from time series. We phenotype gene-deletion strains of fission yeast in 59,350 individual fitness assays in 70 conditions, revealing that colony size and viability provide complementary, independent information. Viability scores obtained from quantifying the redness of phloxine-stained colonies accurately reflect the fraction of live cells within colonies. Pyphe is user-friendly, open-source and fully documented, illustrated by applications to diverse fitness analysis scenarios.

Polar pattern formation induced by contact following locomotion in a multicellular system

Biophysical mechanisms underlying collective cell migration of eukaryotic cells have been studied extensively in recent years. One mechanism that induces cells to correlate their motions is contact inhibition of locomotion, by which cells migrating away from the contact site. Here, we report that tail-following behavior at the contact site, termed contact following locomotion (CFL), can induce a non-trivial collective behavior in migrating cells. We show the emergence of a traveling band showing polar order in a mutant Dictyostelium cell that lacks chemotactic activity. We find that CFL is the cell-cell interaction underlying this phenomenon, enabling a theoretical description of how this traveling band forms. We further show that the polar order phase consists of subpopulations that exhibit characteristic transversal motions with respect to the direction of band propagation. These findings describe a novel mechanism of collective cell migration involving cell-cell interactions capable of inducing traveling band with polar order.

Rapid Accumulation of Motility-Activating Mutations in Resting Liquid Culture of Escherichia coli

Expression of motility genes is a potentially beneficial but costly process in bacteria. Interestingly, many isolate strains of Escherichia coli possess motility genes but have lost the ability to activate them under conditions in which motility is advantageous, raising the question of how they respond to these situations. Through transcriptome profiling of strains in the E. coli single-gene knockout Keio collection, we noticed drastic upregulation of motility genes in many of the deletion strains compared to levels in their weakly motile parent strain (BW25113). We show that this switch to a motile phenotype is not a direct consequence of the genes deleted but is instead due to a variety of secondary mutations that increase the expression of the major motility regulator, FlhDC. Importantly, we find that this switch can be reproduced by growing poorly motile E. coli strains in nonshaking liquid medium overnight but not in shaking liquid medium. Individual isolates after the nonshaking overnight incubations acquired distinct mutations upstream of the flhDC operon, including different insertion sequence (IS) elements and, to a lesser extent, point mutations. The rapidity with which genetic changes sweep through the populations grown without shaking shows that poorly motile strains can quickly adapt to a motile lifestyle by genetic rewiring.IMPORTANCE The ability to tune gene expression in times of need outside preordained regulatory networks is an essential evolutionary process that allows organisms to survive and compete. Here, we show that upon overnight incubation in liquid medium without shaking, populations of largely nonmotile Escherichia coli bacteria can rapidly accumulate mutants that have constitutive motility. This effect contributes to widespread secondary mutations in the single-gene knockout library, the Keio collection. As a result, 49/71 (69%) of the Keio strains tested exhibited various degrees of motility, whereas their parental strain is poorly motile. These observations highlight the plasticity of gene expression even in the absence of preexisting regulatory programs and should raise awareness of procedures for handling laboratory strains of E. coli.

Spatiotemporal establishment of dense bacterial colonies growing on hard agar

The physical interactions of growing bacterial cells with each other and with their surroundings significantly affect the structure and dynamics of biofilms. Here a 3D agent-based model is formulated to describe the establishment of simple bacterial colonies expanding by the physical force of their growth. With a single set of parameters, the model captures key dynamical features of colony growth by non-motile, non EPS-producing E. coli cells on hard agar. The model, supported by experiment on colony growth in different types and concentrations of nutrients, suggests that radial colony expansion is not limited by nutrients as commonly believed, but by mechanical forces. Nutrient penetration instead governs vertical colony growth, through thin layers of vertically oriented cells lifting up their ancestors from the bottom. Overall, the model provides a versatile platform to investigate the influences of metabolic and environmental factors on the growth and morphology of bacterial colonies.

Gene Expression Order Attributed to Genome Reduction and the Steady Cellular State in Escherichia coli

Transcriptomes not only reflect the growth status but also link to the genome in bacteria. To investigate if and how genome or cellular state changes contribute to the gene expression order, the growth profile-associated transcriptomes of an assortment of genetically differentiated Escherichia coli either exponentially growing under varied conditions or in response to environmental disturbance were analyzed. A total of 168 microarray data sets representing 56 transcriptome variations, were categorized by genome size (full length or reduced) and cellular state (steady or unsteady). At the genome-wide level, the power-law distribution of gene expression was found to be significantly disturbed by the genome size but not the cellular state. At the regulatory network level, more networks with improved coordination of growth rates were observed in genome reduction than at the steady state. At the single-gene level, both genome reduction and steady state increased the correlation of gene expression to growth rate, but the enriched gene categories with improved correlations were different. These findings not only illustrate the order of gene expression attributed to genome reduction and steady cellular state but also indicate that the accessory sequences acquired during genome evolution largely participated in the coordination of transcriptomes to growth fitness.

A decay effect of the growth rate associated with genome reduction in Escherichia coli

Background

Bacterial growth is an important topic in microbiology and of crucial importance to better understand living cells. Bacterial growth dynamics are quantitatively examined using various methods to determine the physical, chemical or biological features of growing populations. Due to methodological differences, the exponential growth rate, which is a parameter that is representative of growth dynamics, should be differentiated. Ignoring such differentiation in the growth analysis might overlook somehow slight but significant changes in cellular features of the growing population. Both experimental and theoretical investigations are required to address these issues.

Results

This study experimentally verified the differentiation in growth rates attributed to different methodologies, and demonstrated that the most popular method, optical turbidity, led to the determination of a lower growth rate in comparison to the methods based on colony formation and cellular adenosine triphosphate, due to a decay effect of reading OD₆₀₀ during a population increase. Accordingly, the logistic model, which is commonly applied to the high-throughput growth data reading the OD₆₀₀, was revised by introducing a new parameter: the decay rate, to compensate for the lowered estimation in growth rates. An improved goodness of fit in comparison to the original model was acquired due to this revision. Applying the modified logistic model to hundreds of growth data acquired from an assortment of Escherichia coli strains carrying the reduced genomes led to an intriguing finding of a correlation between the decay rate and the genome size. The decay effect seemed to be partially attributed to the decrease in cell size accompanied by a population increase and was medium dependent.

Conclusions

The present study provides not only an improved theoretical tool for the high-throughput studies on bacterial growth dynamics linking with optical turbidity to biological meaning, but also a novel insight of the genome reduction correlated decay effect, which potentially reflects the changing cellular features during population increase. It is valuable for understanding the genome evolution and the fitness increase in microbial life.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1242-4) contains supplementary material, which is available to authorized users.

PHENOS: a high-throughput and flexible tool for microorganism growth phenotyping on solid media

Background

Microbial arrays, with a large number of different strains on a single plate printed with robotic precision, underpin an increasing number of genetic and genomic approaches. These include Synthetic Genetic Array analysis, high-throughput Quantitative Trait Loci (QTL) analysis and 2-hybrid techniques. Measuring the growth of individual colonies within these arrays is an essential part of many of these techniques but is useful for any work with arrays. Measurement is typically done using intermittent imagery fed into complex image analysis software, which is not especially accurate and is challenging to use effectively. We have developed a simple and fast alternative technique that uses a pinning robot and a commonplace microplate reader to continuously measure the thickness of colonies growing on solid agar, complemented by a technique for normalizing the amount of cells initially printed to each spot of the array in the first place. We have developed software to automate the process of combining multiple sets of readings, subtracting agar absorbance, and visualizing colony thickness changes in a number of informative ways.

Results

The “PHENOS” pipeline (PHENotyping On Solid media), optimized for Saccharomyces yeasts, produces highly reproducible growth curves and is particularly sensitive to low-level growth. We have empirically determined a formula to estimate colony cell count from an absorbance measurement, and shown this to be comparable with estimates from measurements in liquid. We have also validated the technique by reproducing the results of an earlier QTL study done with conventional liquid phenotyping, and found PHENOS to be considerably more sensitive.

Conclusions

“PHENOS” is a cost effective and reliable high-throughput technique for quantifying growth of yeast arrays, and is likely to be equally very useful for a range of other types of microbial arrays. A detailed guide to the pipeline and software is provided with the installation files at https://github.com/gact/phenos.

Electronic supplementary material

The online version of this article (10.1186/s12866-017-1143-y) contains supplementary material, which is available to authorized users.

A tool named Iris for versatile high-throughput phenotyping in microorganisms

Advances in our ability to systematically introduce and track controlled genetic variance in microbes have fueled high-throughput reverse genetics approaches in the past decade. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing insights into the underlying pathways and the overall cellular network organization. Yet, until now all efforts for quantifying microbial macroscopic phenotypes have been restricted to monitoring growth in a small number of model microbes. We developed an image analysis software named Iris, which allows for systematic exploration of a number of orthogonal-to-growth processes, including biofilm formation, colony morphogenesis, envelope biogenesis, sporulation and reporter activity. In addition, Iris provides more sensitive growth measurements than current available software, and is compatible with a variety of different microbes, as well as with endpoint or kinetic data. We used Iris to reanalyze existing chemical genomics data in Escherichia coli and to perform proof-of-principle screens on colony biofilm formation and morphogenesis of different bacterial species and the pathogenic fungus, Candida albicans. Thereby we recapitulated existing knowledge but also identified a plethora of additional genes and pathways involved in both processes.

A robust platform for chemical genomics in bacterial systems

A robust and sensitive platform was developed for chemical-genomics in bacteria. Kinetic acquisitions of colony growth enable calculation of growth rates alongside conventional endpoint volume measurements, generating a wealth of chemical-genetic interactions. This kinetic platform is highly amenable to prokaryotic or eukaryotic strain collections.

While genetic perturbation has been the conventional route to probing bacterial systems, small molecules are showing great promise as probes for cellular complexity. Indeed, systematic investigations of chemical-genetic interactions can provide new insights into cell networks and are often starting points for understanding the mechanism of action of novel chemical probes. We have developed a robust and sensitive platform for chemical-genomic investigations in bacteria. The approach monitors colony volume kinetically using transmissive scanning measurements, enabling acquisition of growth rates and conventional endpoint measurements. We found that chemical-genomic profiles were highly sensitive to concentration, necessitating careful selection of compound concentrations. Roughly 20,000,000 data points were collected for 15 different antibiotics. While 1052 chemical-genetic interactions were identified using the conventional endpoint biomass approach, adding interactions in growth rate resulted in 1564 interactions, a 50–200% increase depending on the drug, with many genes uncharacterized or poorly annotated. The chemical-genetic interaction maps generated from these data reveal common genes likely involved in multidrug resistance. Additionally, the maps identified deletion backgrounds exhibiting class-specific potentiation, revealing conceivable targets for combination approaches to drug discovery. This open platform is highly amenable to kinetic screening of any arrayable strain collection, be it prokaryotic or eukaryotic.

Indispensability of Horizontally Transferred Genes and Its Impact on Bacterial Genome Streamlining

Why are certain bacterial genomes so small and compact? The adaptive genome streamlining hypothesis posits that selection acts to reduce genome size because of the metabolic burden of replicating DNA. To reveal the impact of genome streamlining on cellular traits, we reduced the Escherichia coli genome by up to 20% by deleting regions which have been repeatedly subjects of horizontal transfer in nature. Unexpectedly, horizontally transferred genes not only confer utilization of specific nutrients and elevate tolerance to stresses, but also allow efficient usage of resources to build new cells, and hence influence fitness in routine and stressful environments alike. Genome reduction affected fitness not only by gene loss, but also by induction of a general stress response. Finally, we failed to find evidence that the advantage of smaller genomes would be due to a reduced metabolic burden of replicating DNA or a link with smaller cell size. We conclude that as the potential energetic benefit gained by deletion of short genomic segments is vanishingly small compared with the deleterious side effects of these deletions, selection for reduced DNA synthesis costs is unlikely to shape the evolution of small genomes.

Predictive analytics of environmental adaptability in multi-omic network models

Bacterial phenotypic traits and lifestyles in response to diverse environmental conditions depend on changes in the internal molecular environment. However, predicting bacterial adaptability is still difficult outside of laboratory controlled conditions. Many molecular levels can contribute to the adaptation to a changing environment: pathway structure, codon usage, metabolism. To measure adaptability to changing environmental conditions and over time, we develop a multi-omic model of Escherichia coli that accounts for metabolism, gene expression and codon usage at both transcription and translation levels. After the integration of multiple omics into the model, we propose a multiobjective optimization algorithm to find the allowable and optimal metabolic phenotypes through concurrent maximization or minimization of multiple metabolic markers. In the condition space, we propose Pareto hypervolume and spectral analysis as estimators of short term multi-omic (transcriptomic and metabolic) evolution, thus enabling comparative analysis of metabolic conditions. We therefore compare, evaluate and cluster different experimental conditions, models and bacterial strains according to their metabolic response in a multidimensional objective space, rather than in the original space of microarray data. We finally validate our methods on a phenomics dataset of growth conditions. Our framework, named METRADE, is freely available as a MATLAB toolbox.

Identification of essential genes and synthetic lethal gene combinations in Escherichia coli K-12

Here we describe the systematic identification of single genes and gene pairs, whose knockout causes lethality in Escherichia coli K-12. During construction of precise single-gene knockout library of E. coli K-12, we identified 328 essential gene candidates for growth in complex (LB) medium. Upon establishment of the Keio single-gene deletion library, we undertook the development of the ASKA single-gene deletion library carrying a different antibiotic resistance. In addition, we developed tools for identification of synthetic lethal gene combinations by systematic construction of double-gene knockout mutants. We introduce these methods herein.

Genome-scale identification and characterization of moonlighting proteins

BACKGROUND

Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.

RESULTS

First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter's primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.

CONCLUSION

Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.

REVIEWERS

This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

GenoBase: comprehensive resource database of Escherichia coli K-12

Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources.