The E. coli molecular phenotype under different growth conditions

Analysis of bacterial transcriptome and epitranscriptome using nanopore direct RNA sequencing

Bacterial gene expression is a complex process involving extensive regulatory mechanisms. Along with growing interests in this field, Nanopore Direct RNA Sequencing (DRS) provides a promising platform for rapid and comprehensive characterization of bacterial RNA biology. However, the DRS of bacterial RNA is currently deficient in the yield of mRNA-mapping reads and has yet to be exploited for transcriptome-wide RNA modification mapping. Here, we showed that pre-processing of bacterial total RNA (size selection followed by ribosomal RNA depletion and polyadenylation) guaranteed high throughputs of sequencing data and considerably increased the amount of mRNA reads. This way, complex transcriptome architectures were reconstructed for Escherichia coli and Staphylococcus aureus and extended the boundaries of 225 known E. coli operons and 89 defined S. aureus operons. Utilizing unmodified in vitro-transcribed (IVT) RNA libraries as a negative control, several Nanopore-based computational tools globally detected putative modification sites in the E. coli and S. aureus transcriptomes. Combined with Next-Generation Sequencing-based N6-methyladenosine (m6A) detection methods, 75 high-confidence m6A candidates were identified in the E. coli protein-coding transcripts, while none were detected in S. aureus. Altogether, we demonstrated the potential of Nanopore DRS in systematic and convenient transcriptome and epitranscriptome analysis.

'Wild Type'

In this opinion piece, we consider the meaning of the term 'wild type' in the context of microbiology. This is especially pertinent in the post-genomic era, where we have a greater awareness of species diversity than ever before. Genomic heterogeneity, in vitro evolution/selection pressures, definition of 'the wild', the size and importance of the pan-genome, gene-gene interactions (epistasis), and the nature of the 'wild-type gene' are all discussed. We conclude that wild type is an outdated and even misleading phrase that should be gradually phased out.

Involvement of Escherichia coli YbeX/CorC in ribosomal metabolism

YbeX of Escherichia coli, a member of the CorC protein family, is encoded in the same operon with ribosome-associated proteins YbeY and YbeZ. Here, we report the involvement of YbeX in ribosomal metabolism. The ΔybeX cells accumulate distinct 16S rRNA degradation intermediates in the 30S particles and the 70S ribosomes. E. coli lacking ybeX has a lengthened lag phase upon outgrowth from the stationary phase. This growth phenotype is heterogeneous at the individual cell level and especially prominent under low extracellular magnesium levels. The ΔybeX strain is sensitive to elevated growth temperatures and to several ribosome-targeting antibiotics that have in common the ability to induce the cold shock response in E. coli. Although generally milder, the phenotypes of the ΔybeX mutant overlap with those caused by ybeY deletion. A genetic screen revealed partial compensation of the ΔybeX growth phenotype by the overexpression of YbeY. These findings indicate an interconnectedness among the ybeZYX operon genes, highlighting their roles in ribosomal assembly and/or degradation.

Promoter recruitment drives the emergence of proto-genes in a long-term evolution experiment with Escherichia coli

The phenomenon of de novo gene birth-the emergence of genes from non-genic sequences-has received considerable attention due to the widespread occurrence of genes that are unique to particular species or genomes. Most instances of de novo gene birth have been recognized through comparative analyses of genome sequences in eukaryotes, despite the abundance of novel, lineage-specific genes in bacteria and the relative ease with which bacteria can be studied in an experimental context. Here, we explore the genetic record of the Escherichia coli long-term evolution experiment (LTEE) for changes indicative of "proto-genic" phases of new gene birth in which non-genic sequences evolve stable transcription and/or translation. Over the time span of the LTEE, non-genic regions are frequently transcribed, translated and differentially expressed, with levels of transcription across low-expressed regions increasing in later generations of the experiment. Proto-genes formed downstream of new mutations result either from insertion element activity or chromosomal translocations that fused preexisting regulatory sequences to regions that were not expressed in the LTEE ancestor. Additionally, we identified instances of proto-gene emergence in which a previously unexpressed sequence was transcribed after formation of an upstream promoter, although such cases were rare compared to those caused by recruitment of preexisting promoters. Tracing the origin of the causative mutations, we discovered that most occurred early in the history of the LTEE, often within the first 20,000 generations, and became fixed soon after emergence. Our findings show that proto-genes emerge frequently within evolving populations, can persist stably, and can serve as potential substrates for new gene formation.

Dynamic remodeling of Escherichia coli interactome in response to environmental perturbations

Proteins play an essential role in the vital biological processes governing cellular functions. Most proteins function as members of macromolecular machines, with the network of interacting proteins revealing the molecular mechanisms driving the formation of these complexes. Profiling the physiology-driven remodeling of these interactions within different contexts constitutes a crucial component to achieving a comprehensive systems-level understanding of interactome dynamics. Here, we apply co-fractionation mass spectrometry and computational modeling to quantify and profile the interactions of ∼2000 proteins in the bacterium Escherichia coli cultured under 10 distinct culture conditions. The resulting quantitative co-elution patterns revealed large-scale condition-dependent interaction remodeling among protein complexes involved in diverse biochemical pathways in response to the unique environmental challenges. The network-level analysis highlighted interactome-wide biophysical properties and structural patterns governing interaction remodeling. Our results provide evidence of the local and global plasticity of the E. coli interactome along with a rigorous generalizable framework to define protein interaction specificity. We provide an accompanying interactive web application to facilitate the exploration of these rewired networks.

Creating Polyploid Escherichia Coli and Its Application in Efficient L-Threonine Production

Prokaryotic genomes are generally organized in haploid. In synthetic biological research, efficient chassis cells must be constructed to produce bio-based products. Here, the essential division of the ftsZ gene to create functional polyploid E. coli is regulated. The artificial polyploid E. coli containing 2-4 chromosomes is confirmed through PCR amplification, terminator localization, and flow cytometry. The polyploid E. coli exhibits a larger cell size, and its low pH tolerance and acetate resistance are stronger than those of haploid E. coli. Transcriptome analysis shows that the genes of the cell's main functional pathways are significantly upregulated in the polyploid E. coli. These advantages of the polyploid E. coli results in the highest reported L-threonine yield (160.3 g L-1 ) in fed-batch fermentation to date. In summary, an easy and convenient method for constructing polyploid E. coli and demonstrated its application in L-threonine production is developed. This work provides a new approach for creating an excellent host strain for biochemical production and studying the evolution of prokaryotes and their chromosome functions.

Elucidating the dynamic remodelling of Escherichia coli interactome in different growth conditions using multiplex co-fractionation MS (mCF-MS)

Most proteins function by forming complexes within a dynamic interconnected network that underlies various biological mechanisms. To systematically investigate such interactomes, high-throughput techniques, including CF-MS, have been developed to capture, identify, and quantify protein-protein interactions (PPIs) on a large scale. Compared to other techniques, CF-MS allows the global identification and quantification of native protein complexes in one setting, without genetic manipulation. Furthermore, quantitative CF-MS can potentially elucidate the distribution of a protein in multiple co-elution features, informing the stoichiometries and dynamics of a target protein complex. In this issue, Youssef et al. (Proteomics 2023, 00, e2200404) combined multiplex CF-MS and a new algorithm to study the dynamics of the PPI network for Escherichia coli grown under ten different conditions. Although the results demonstrated that most proteins remained stable, the authors were able to detect disrupted interactions that were growth condition specific. Further bioinformatics analyses also revealed the biophysical properties and structural patterns that govern such a response.

The global anaerobic metabolism regulator fnr is necessary for the degradation of food dyes and drugs by Escherichia coli

IMPORTANCE

This work has broad relevance due to the ubiquity of dyes containing azo bonds in food and drugs. We report that azo dyes can be degraded by human gut bacteria through both enzymatic and nonenzymatic mechanisms, even from a single gut bacterial species. Furthermore, we revealed that environmental factors, oxygen, and L-Cysteine control the ability of E. coli to degrade azo dyes due to their impacts on bacterial transcription and metabolism. These results open up new opportunities to manipulate the azoreductase activity of the gut microbiome through the manipulation of host diet, suggest that azoreductase potential may be altered in patients suffering from gastrointestinal disease, and highlight the importance of studying bacterial enzymes for drug metabolism in their natural cellular and ecological context.

System-wide optimization of an orthogonal translation system with enhanced biological tolerance

Over the past two decades, synthetic biological systems have revolutionized the study of cellular physiology. The ability to site-specifically incorporate biologically relevant non-standard amino acids using orthogonal translation systems (OTSs) has proven particularly useful, providing unparalleled access to cellular mechanisms modulated by post-translational modifications, such as protein phosphorylation. However, despite significant advances in OTS design and function, the systems-level biology of OTS development and utilization remains underexplored. In this study, we employ a phosphoserine OTS (pSerOTS) as a model to systematically investigate global interactions between OTS components and the cellular environment, aiming to improve OTS performance. Based on this analysis, we design OTS variants to enhance orthogonality by minimizing host process interactions and reducing stress response activation. Our findings advance understanding of system-wide OTS:host interactions, enabling informed design practices that circumvent deleterious interactions with host physiology while improving OTS performance and stability. Furthermore, our study emphasizes the importance of establishing a pipeline for systematically profiling OTS:host interactions to enhance orthogonality and mitigate mechanisms underlying OTS-mediated host toxicity.

Engineering tRNA abundances for synthetic cellular systems

Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test.

Impact of Growth Rate on the Protein-mRNA Ratio in Pseudomonas aeruginosa

Our understanding of how bacterial pathogens colonize and persist during human infection has been hampered by the limited characterization of bacterial physiology during infection and a research bias toward in vitro, fast-growing bacteria. Recent research has begun to address these gaps in knowledge by directly quantifying bacterial mRNA levels during human infection, with the goal of assessing microbial community function at the infection site. However, mRNA levels are not always predictive of protein levels, which are the primary functional units of a cell. Here, we used carefully controlled chemostat experiments to examine the relationship between mRNA and protein levels across four growth rates in the bacterial pathogen Pseudomonas aeruginosa. We found a genome-wide positive correlation between mRNA and protein abundances across all growth rates, with genes required for P. aeruginosa viability having stronger correlations than nonessential genes. We developed a statistical method to identify genes whose mRNA abundances poorly predict protein abundances and calculated an RNA-to-protein (RTP) conversion factor to improve mRNA predictions of protein levels. The application of the RTP conversion factor to publicly available transcriptome data sets was highly robust, enabling the more accurate prediction of P. aeruginosa protein levels across strains and growth conditions. Finally, the RTP conversion factor was applied to P. aeruginosa human cystic fibrosis (CF) infection transcriptomes to provide greater insights into the functionality of this bacterium in the CF lung. This study addresses a critical problem in infection microbiology by providing a framework for enhancing the functional interpretation of bacterial human infection transcriptome data. IMPORTANCE Our understanding of bacterial physiology during human infection is limited by the difficulty in assessing bacterial function at the infection site. Recent studies have begun to address this question by quantifying bacterial mRNA levels in human-derived samples using transcriptomics. One challenge for these studies is the poor predictivity of mRNA for protein levels for some genes. Here, we addressed this challenge by measuring the transcriptomes and proteomes of P. aeruginosa grown at four growth rates. Our results revealed that the growth rate does not impact the genome-wide correlation of mRNA and protein levels. We used statistical methods to identify the genes for which mRNA and protein were poorly correlated and developed an RNA-to-protein (RTP) conversion factor that improved the predictivity of protein levels across strains and growth conditions. Our results provide new insights into mRNA-protein correlations and tools to enhance our understanding of bacterial physiology from transcriptome data.

About the dark corners in the gene function space of Escherichia coli remaining without illumination by scientific literature

BACKGROUND

Although Escherichia coli (E. coli) is the most studied prokaryote organism in the history of life sciences, many molecular mechanisms and gene functions encoded in its genome remain to be discovered. This work aims at quantifying the illumination of the E. coli gene function space by the scientific literature and how close we are towards the goal of a complete list of E. coli gene functions.

RESULTS

The scientific literature about E. coli protein-coding genes has been mapped onto the genome via the mentioning of names for genomic regions in scientific articles both for the case of the strain K-12 MG1655 as well as for the 95%-threshold softcore genome of 1324 E. coli strains with known complete genome. The article match was quantified with the ratio of a given gene name's occurrence to the mentioning of any gene names in the paper. The various genome regions have an extremely uneven literature coverage. A group of elite genes with ≥ 100 full publication equivalents (FPEs, FPE = 1 is an idealized publication devoted to just a single gene) attracts the lion share of the papers. For K-12, ~ 65% of the literature covers just 342 elite genes; for the softcore genome, ~ 68% of the FPEs is about only 342 elite gene families (GFs). We also find that most genes/GFs have at least one mentioning in a dedicated scientific article (with the exception of at least 137 protein-coding transcripts for K-12 and 26 GFs from the softcore genome). Whereas the literature growth rates were highest for uncharacterized or understudied genes until 2005-2010 compared with other groups of genes, they became negative thereafter. At the same time, literature for anyhow well-studied genes started to grow explosively with threshold T10 (≥ 10 FPEs). Typically, a body of ~ 20 actual articles generated over ~ 15 years of research effort was necessary to reach T10. Lineage-specific co-occurrence analysis of genes belonging to the accessory genome of E. coli together with genomic co-localization and sequence-analytic exploration hints previously completely uncharacterized genes yahV and yddL being associated with osmotic stress response/motility mechanisms.

CONCLUSION

If the numbers of scientific articles about uncharacterized and understudied genes remain at least at present levels, full gene function lists for the strain K-12 MG1655 and the E. coli softcore genome are in reach within the next 25-30 years. Once the literature body for a gene crosses 10 FPEs, most of the critical fundamental research risk appears overcome and steady incremental research becomes possible.

An integrated transcriptomics-functional genomics approach reveals a small RNA that modulates Bacteroides thetaiotaomicron sensitivity to tetracyclines

Gene expression plasticity allows bacteria to adapt to diverse environments, tie their metabolism to available nutrients, and cope with stress. This is particularly relevant in a niche as dynamic and hostile as the human intestinal tract, yet transcriptional networks remain largely unknown in gut Bacteroides spp. Here, we map transcriptional units and profile their expression levels in Bacteroides thetaiotaomicron over a suite of 15 defined experimental conditions that are relevant in vivo , such as variation of temperature, pH, and oxygen tension, exposure to antibiotic stress, and growth on simple carbohydrates or on host mucin-derived glycans. Thereby, we infer stress- and carbon source-specific transcriptional regulons, including conditional expression of capsular polysaccharides and polysaccharide utilization loci, and expand the annotation of small regulatory RNAs (sRNAs) in this organism. Integrating this comprehensive expression atlas with transposon mutant fitness data, we identify conditionally important sRNAs. One example is MasB, whose inactivation led to increased bacterial tolerance of tetracyclines. Using MS2 affinity purification coupled with RNA sequencing, we predict targets of this sRNA and discuss their potential role in the context of the MasB-associated phenotype. Together, this transcriptomic compendium in combination with functional sRNA genomics-publicly available through a new iteration of the 'Theta-Base' web browser (www.helmholtz-hiri.de/en/datasets/bacteroides-v2)-constitutes a valuable resource for the microbiome and sRNA research communities alike.

Enzyme expression kinetics by Escherichia coli during transition from rich to minimal media depends on proteome reserves

Bacterial fitness depends on adaptability to changing environments. In rich growth medium, which is replete with amino acids, Escherichia coli primarily expresses protein synthesis machineries, which comprise ~40% of cellular proteins and are required for rapid growth. Upon transition to minimal medium, which lacks amino acids, biosynthetic enzymes are synthesized, eventually reaching ~15% of cellular proteins when growth fully resumes. We applied quantitative proteomics to analyse the timing of enzyme expression during such transitions, and established a simple positive relation between the onset time of enzyme synthesis and the fractional enzyme 'reserve' maintained by E. coli while growing in rich media. We devised and validated a coarse-grained kinetic model that quantitatively captures the enzyme recovery kinetics in different pathways, solely on the basis of proteomes immediately preceding the transition and well after its completion. Our model enables us to infer regulatory strategies underlying the 'as-needed' gene expression programme adopted by E. coli.

The RNA repair proteins RtcAB regulate transcription activator RtcR via its CRISPR-associated Rossmann fold domain

CRISPR-associated Rossmann fold (CARF) domain signaling underpins modulation of CRISPR-Cas nucleases; however, the RtcR CARF domain controls expression of two conserved RNA repair enzymes, cyclase RtcA and ligase RtcB. Here, we demonstrate that RtcAB are required for RtcR-dependent transcription activation and directly bind to RtcR CARF. RtcAB catalytic activity is not required for complex formation with CARF, but is essential yet not sufficient for RtcRAB-dependent transcription activation, implying the need for an additional RNA repair-dependent activating signal. This signal differs from oligoadenylates, a known ligand of CARF domains, and instead appears to originate from the translation apparatus: RtcB repairs a tmRNA that rescues stalled ribosomes and increases translation elongation speed. Taken together, our data provide evidence for an expanded range for CARF domain signaling, including the first evidence of its control via in trans protein-protein interactions, and a feed-forward mechanism to regulate RNA repair required for a functioning translation apparatus.

Conversion of mammalian cell culture media waste to microbial fermentation feed efficiently supports production of recombinant protein by Escherichia coli

Deriving new value from waste streams through secondary processes is a central aim of the circular bioeconomy. In this study we investigate whether chemically defined spent media (CDSM) waste from cell culture bioprocess can be recycled and used as a feed in secondary microbial fermentation to produce new recombinant protein products. Our results show that CDSM supplemented with 2% glycerol supported a specific growth rate of E. coli cultures equivalent to that achieved using a nutritionally rich microbiological media (LB). The titre of recombinant protein produced following induction in a 4-hour expression screen was approximately equivalent in the CDSM fed cultures to that of baseline, and this was maintained in a 16-hr preparative fermentation. To understand the protein production achieved in CDSM fed culture we performed a quantitative analysis of proteome changes in the E. coli using mass spectrometry. This analysis revealed significant upregulation of protein synthesis machinery enzymes and significant downregulation of carbohydrate metabolism enzymes. We conclude that spent cell culture media, which represents 100s of millions of litres of waste generated by the bioprocessing industry annually, may be valorized as a feed resource for the production of recombinant proteins in secondary microbial fermentations. Data is available via ProteomeXchange with identifier PXD026884.

Indole modulates cooperative protein-protein interactions in the flagellar motor

Indole is a major component of the bacterial exometabolome, and the mechanisms for its wide-ranging effects on bacterial physiology are biomedically significant, although they remain poorly understood. Here, we determined how indole modulates the functions of a widely conserved motility apparatus, the bacterial flagellum. Our experiments in Escherichia coli revealed that indole influences the rotation rates and reversals in the flagellum’s direction of rotation via multiple mechanisms. At concentrations higher than 1 mM, indole decreased the membrane potential to dissipate the power available for the rotation of the motor that operates the flagellum. Below 1 mM, indole did not dissipate the membrane potential. Instead, experiments and modeling indicated that indole weakens cooperative protein interactions within the flagellar complexes to inhibit motility. The metabolite also induced reversals in the rotational direction of the motor to promote a weak chemotactic response, even when the chemotaxis response regulator, CheY, was lacking. Experiments further revealed that indole does not require the transporter Mtr to cross the membrane and influence motor functions. Based on these findings, we propose that indole modulates intra- and inter-protein interactions in the cell to influence several physiological functions.

Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells

The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role.

Proteome Expression and Survival Strategies of a Proteorhodopsin-Containing Vibrio Strain under Carbon and Nitrogen Limitation

Photoheterotrophy is a widespread mode of microbial metabolism, notably in the oligotrophic surface ocean, where microbes experience chronic nutrient limitation. One especially widespread form of photoheterotrophy is based on proteorhodopsin (PR), which uses light to generate proton motive force that can drive ATP synthesis, flagellar movement, or nutrient uptake. To clarify the physiological benefits conferred by PR under nutrient stress conditions, we quantified protein-level gene expression of Vibrio campbellii CAIM 519 under both carbon and nitrogen limitation and under both light and dark conditions. Using a novel membrane proteomics strategy, we determined that PR expression is higher under C limitation than N limitation but is not light regulated. Despite expression of PR photosystems, V. campbellii does not exhibit any growth or survival advantages in the light and only a few proteins show significant expression differences between light and dark conditions. While protein-level proteorhodopsin expression in V. campbellii is clearly responsive to nutrient limitation, photoheterotrophy does not appear to play a central role in the survival physiology of this organism under these nutrient stress conditions. C limitation and N limitation, however, result in very different survival responses: under N-limited conditions, viability declines, cultivability is lost rapidly, central carbon flux through the Entner-Doudoroff pathway is increased, and ammonium is assimilated via the GS-GOGAT pathway. In contrast, C limitation drives cell dwarfing with maintenance of viability, as well as utilization of the glyoxylate shunt, glutamate dehydrogenase and anaplerotic C fixation, and a stringent response mediated by the Pho regulon.

IMPORTANCE Understanding the nutrient stress responses of proteorhodopsin-bearing microbes like Vibrio campbellii yields insights into microbial contributions to nutrient cycling, lifestyles of emerging pathogens in aquatic environments, and protein-level adaptations implemented during times of nutrient limitation. In addition to its broad taxonomic and geographic prevalence, the physiological role of PR is diverse, so we developed a novel proteomics strategy to quantify its expression at the protein level. We found that proteorhodopsin expression levels in this wild-type photoheterotroph under these experimental conditions, while higher under C than under N limitation, do not afford measurable light-driven growth or survival advantages. Additionally, this work links differential protein expression patterns between C- and N-limited cultures to divergent stationary-phase survival phenotypes.

Design, mutate, screen: Multiplexed creation and arrayed screening of synchronized genetic clocks

A major goal in synthetic biology is coordinating cellular behavior using cell-cell interactions; however, designing and testing complex genetic circuits that function only in large populations remains challenging. Although directed evolution has commonly supplemented rational design methods for synthetic gene circuits, this method relies on the efficient screening of mutant libraries for desired phenotypes. Recently, multiple techniques have been developed for identifying dynamic phenotypes from large, pooled libraries. These technologies have advanced library screening for single-cell, time-varying phenotypes but are currently incompatible with population-level phenotypes dependent on cell-cell communication. Here, we utilize directed mutagenesis and multiplexed microfluidics to develop an arrayed-screening workflow for dynamic, population-level genetic circuits. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and discover variants with different period-amplitude characteristics. Lastly, we utilize our screening workflow to construct a transcriptionally regulated synchronized oscillator that functions over long timescales. A record of this paper's transparent peer review process is included in the supplemental information.

Universal Constraints on Protein Evolution in the Long-Term Evolution Experiment with Escherichia coli

Although it is well known that abundant proteins evolve slowly across the tree of life, there is little consensus for why this is true. Here, I report that abundant proteins evolve slowly in the hypermutator populations of Lenski's long-term evolution experiment with Escherichia coli (LTEE). Specifically, the density of all observed mutations per gene, as measured in metagenomic time series covering 60,000 generations of the LTEE, significantly anticorrelates with mRNA abundance, protein abundance, and degree of protein-protein interaction. The same pattern holds for nonsynonymous mutation density. However, synonymous mutation density, measured across the LTEE hypermutator populations, positively correlates with protein abundance. These results show that universal constraints on protein evolution are visible in data spanning three decades of experimental evolution. Therefore, it should be possible to design experiments to answer why abundant proteins evolve slowly.

From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non-metabolic stresses, and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of large-scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.

Rapid Detection of Escherichia coli Antibiotic Susceptibility Using Live/Dead Spectrometry for Lytic Agents

Antibiotic resistance is a serious threat to public health. The empiric use of the wrong antibiotic occurs due to urgency in treatment combined with slow, culture-based diagnostic techniques. Inappropriate antibiotic choice can promote the development of antibiotic resistance. We investigated live/dead spectrometry using a fluorimeter (Optrode) as a rapid alternative to culture-based techniques through application of the LIVE/DEAD® BacLightTM Bacterial Viability Kit. Killing was detected by the Optrode in near real-time when Escherichia coli was treated with lytic antibiotics-ampicillin and polymyxin B-and stained with SYTO 9 and/or propidium iodide. Antibiotic concentration, bacterial growth phase, and treatment time used affected the efficacy of this detection method. Quantification methods of the lethal action and inhibitory action of the non-lytic antibiotics, ciprofloxacin and chloramphenicol, respectively, remain to be elucidated.

Fluorescent bacterial biosensor E. coli/pTdcR-TurboYFP sensitive to terahertz radiation

A fluorescent biosensor E. coli/pTdcR-TurboYFP sensitive to terahertz (THz) radiation was developed via transformation of Escherichia coli (E. coli) cells with plasmid, in which the promotor of the tdcR gene controls the expression of yellow fluorescent protein TurboYFP. The biosensor was exposed to THz radiation in various vessels and nutrient media. The threshold and dynamics of fluorescence were found to depend on irradiation conditions. Heat shock or chemical stress yielded the absence of fluorescence induction. The biosensor is applicable to studying influence of THz radiation on the activity of tdcR promotor that is involved in the transport and metabolism of threonine and serine in E. coli.

Transcriptomic analysis of a Clostridium thermocellum strain engineered to utilize xylose: responses to xylose versus cellobiose feeding

Clostridium (Ruminiclostridium) thermocellum is recognized for its ability to ferment cellulosic biomass directly, but it cannot naturally grow on xylose. Recently, C. thermocellum (KJC335) was engineered to utilize xylose through expressing a heterologous xylose catabolizing pathway. Here, we compared KJC335′s transcriptomic responses to xylose versus cellobiose as the primary carbon source and assessed how the bacteria adapted to utilize xylose. Our analyses revealed 417 differentially expressed genes (DEGs) with log₂ fold change (FC) >|1| and 106 highly DEGs (log₂ FC >|2|). Among the DEGs, two putative sugar transporters, cbpC and cbpD, were up-regulated, suggesting their contribution to xylose transport and assimilation. Moreover, the up-regulation of specific transketolase genes (tktAB) suggests the importance of this enzyme for xylose metabolism. Results also showed remarkable up-regulation of chemotaxis and motility associated genes responding to xylose feeding, as well as widely varying gene expression in those encoding cellulosomal enzymes. For the down-regulated genes, several were categorized in gene ontology terms oxidation–reduction processes, ATP binding and ATPase activity, and integral components of the membrane. This study informs potentially critical, enabling mechanisms to realize the conceptually attractive Next-Generation Consolidated BioProcessing approach where a single species is sufficient for the co-fermentation of cellulose and hemicellulose.

Ionizing Radiation-induced Proteomic Oxidation in Escherichia coli

Recent work has begun to investigate the role of protein damage in cell death because of ionizing radiation (IR) exposure, but none have been performed on a proteome-wide basis, nor have they utilized MS (MS) to determine chemical identity of the amino acid side chain alteration. Here, we use Escherichia coli to perform the first MS analysis of IR-treated intact cells on a proteome scale. From quintuplicate IR-treated (1000 Gy) and untreated replicates, we successfully quantified 13,262 peptides mapping to 1938 unique proteins. Statistically significant, but low in magnitude (<2-fold), IR-induced changes in peptide abundance were observed in 12% of all peptides detected, although oxidative alterations were rare. Hydroxylation (+15.99 Da) was the most prevalent covalent adduct detected. In parallel with these studies on E. coli, identical experiments with the IR-resistant bacterium, Deinococcus radiodurans, revealed orders of magnitude less effect of IR on the proteome. In E. coli, the most significant target of IR by a wide margin was glyceraldehyde 3'-phosphate dehydrogenase (GAPDH), in which the thiol side chain of the catalytic Cys residue was oxidized to sulfonic acid. The same modification was detected in IR-treated human breast carcinoma cells. Sensitivity of GAPDH to reactive oxygen species (ROS) has been described previously in microbes and here, we present GAPDH as an immediate, primary target of IR-induced oxidation across all domains of life.

Structural Basis of the Subcellular Topology Landscape of Escherichia coli

Cellular proteomes are distributed in multiple compartments: on DNA, ribosomes, on and inside membranes, or they become secreted. Structural properties that allow polypeptides to occupy subcellular niches, particularly to after crossing membranes, remain unclear. We compared intrinsic and extrinsic features in cytoplasmic and secreted polypeptides of the Escherichia coli K-12 proteome. Structural features between the cytoplasmome and secretome are sharply distinct, such that a signal peptide-agnostic machine learning tool distinguishes cytoplasmic from secreted proteins with 95.5% success. Cytoplasmic polypeptides are enriched in aliphatic, aromatic, charged and hydrophobic residues, unique folds and higher early folding propensities. Secretory polypeptides are enriched in polar/small amino acids, β folds, have higher backbone dynamics, higher disorder and contact order and are more often intrinsically disordered. These non-random distributions and experimental evidence imply that evolutionary pressure selected enhanced secretome flexibility, slow folding and looser structures, placing the secretome in a distinct protein class. These adaptations protect the secretome from premature folding during its cytoplasmic transit, optimize its lipid bilayer crossing and allowed it to acquire cell envelope specific chemistries. The latter may favor promiscuous multi-ligand binding, sensing of stress and cell envelope structure changes. In conclusion, enhanced flexibility, slow folding, looser structures and unique folds differentiate the secretome from the cytoplasmome. These findings have wide implications on the structural diversity and evolution of modern proteomes and the protein folding problem.

Predicting the decision making chemicals used for bacterial growth

Predicting the contribution of media components to bacterial growth was first initiated by introducing machine learning to high-throughput growth assays. A total of 1336 temporal growth records corresponding to 225 different media, which were composed of 13 chemical components, were generated. The growth rate and saturated density of each growth curve were automatically calculated with the newly developed data processing program. To identify the decision making factors related to growth among the 13 chemicals, big datasets linking the growth parameters to the chemical combinations were subjected to decision tree learning. The results showed that the only carbon source, glucose, determined bacterial growth, but it was not the first priority. Instead, the top decision making chemicals in relation to the growth rate and saturated density were ammonium and ferric ions, respectively. Three chemical components (NH₄⁺, Mg²⁺ and glucose) commonly appeared in the decision trees of the growth rate and saturated density, but they exhibited different mechanisms. The concentration ranges for fast growth and high density were overlapped for glucose but distinguished for NH₄⁺ and Mg²⁺. The results suggested that these chemicals were crucial in determining the growth speed and growth maximum in either a universal use or a trade-off manner. This differentiation might reflect the diversity in the resource allocation mechanisms for growth priority depending on the environmental restrictions. This study provides a representative example for clarifying the contribution of the environment to population dynamics through an innovative viewpoint of employing modern data science within traditional microbiology to obtain novel findings.

Designing Metabolic Division of Labor in Microbial Communities

Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A "gedanken" (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

Predicting bacterial growth conditions from mRNA and protein abundances

Cells respond to changing nutrient availability and external stresses by altering the expression of individual genes. Condition-specific gene expression patterns may thus provide a promising and low-cost route to quantifying the presence of various small molecules, toxins, or species-interactions in natural environments. However, whether gene expression signatures alone can predict individual environmental growth conditions remains an open question. Here, we used machine learning to predict 16 closely-related growth conditions using 155 datasets of E. coli transcript and protein abundances. We show that models are able to discriminate between different environmental features with a relatively high degree of accuracy. We observed a small but significant increase in model accuracy by combining transcriptome and proteome-level data, and we show that measurements from stationary phase cells typically provide less useful information for discriminating between conditions as compared to exponentially growing populations. Nevertheless, with sufficient training data, gene expression measurements from a single species are capable of distinguishing between environmental conditions that are separated by a single environmental variable.

Impact of Active Metabolism on Chlamydia trachomatis Elementary Body Transcript Profile and Infectivity

Bacteria of the genus Chlamydia include the significant human pathogens Chlamydia trachomatis and C. pneumoniae All chlamydiae are obligate intracellular parasites that depend on infection of a host cell and transition through a biphasic developmental cycle. Following host cell invasion by the infectious elementary body (EB), the pathogen transitions to the replicative but noninfectious reticulate body (RB). Differentiation of the RB back to the EB is essential to generate infectious progeny. While the EB form has historically been regarded as metabolically inert, maintenance of infectivity during incubation with specific nutrients has revealed active maintenance of the infectious phenotype. Using transcriptome sequencing, we show that the transcriptome of extracellular EBs incubated under metabolically stimulating conditions does not cluster with germinating EBs but rather with the transcriptome of EBs isolated directly from infected cells. In addition, the transcriptional profile of the extracellular metabolizing EBs more closely resembled that of EB production than germination. Maintenance of infectivity of extracellular EBs was achieved by metabolizing chemically diverse compounds, including glucose 6-phosphate, ATP, and amino acids, all of which can be found in extracellular environments, including mucosal secretions. We further show that the EB cell type actively maintains infectivity in the inclusion after terminal differentiation. Overall, these findings contribute to the emerging understanding that the EB cell form is actively maintained through metabolic processes after terminal differentiation to facilitate prolonged infectivity within the inclusion and under host cell free conditions, for example, following deposition at mucosal surfaces.IMPORTANCE Chlamydiae are obligate intracellular Gram-negative bacteria that are responsible for a wide range of diseases in both animal and human hosts. According to the Centers for Disease Control and Prevention, C. trachomatis is the most frequently reported sexually transmitted infection in the United States, costing the American health care system nearly $2.4 billion annually. Every year, there are over 4 million new cases of Chlamydia infections in the United States and an estimated 100 million cases worldwide. To cause disease, Chlamydia must successfully complete its complex biphasic developmental cycle, alternating between an infectious cell form (EB) specialized for initiating entry into target cells and a replicative form (RB) specialized for creating and maintaining the intracellular replication niche. The EB cell form has historically been considered metabolically quiescent, a passive entity simply waiting for contact with a host cell to initiate the next round of infection. Recent studies and data presented here demonstrate that the EB maintains its infectious phenotype by actively metabolizing a variety of nutrients. Therefore, the EB appears to have an active role in chlamydial biology, possibly within multiple environments, such as mucosal surfaces, fomites, and inside the host cell after formation.

[Influence of cultivation conditions on the proteomic profile of Mycobacterium tuberculosis H37RV]

Comparative proteomic profiling of M. tuberculosis H37Rv strains cultured on two different nutrient media, Levenstein-Jensen and Middlebrook 7H11, was performed using a label-free LC-MS/MS approach. It was shown that results obtained from two media possessed high convergence. The only difference was observed in the representation of fumarate reductase FrdB, its abundance was higher in the mycobacterial cells cultured on Levenstein-Jensen medium. The correlation analysis of biological repeats revealed the high convergence of the results obtained from Middlebrook 7H11 medium. Thus, we can conclude that the use of the Middlebrook 7H11 medium is most appropriate in the scientific laboratory.