Gut-associated microbes are present and active in the pig nasal cavity.

The nasal microbiota is a key contributor to animal health, and characterizing the nasal microbiota composition is an important step towards elucidating the role of its different members. Efforts to characterize the nasal microbiota composition of domestic pigs and other farm animals frequently report the presence of bacteria that are typically found in the gut, including many anaerobes from the Bacteroidales and Clostridiales orders. However, the in vivo role of these gut-microbiota associated taxa is currently unclear. Here, we tackled this issue by examining the prevalence, origin, and activity of these taxa in the nasal microbiota of piglets. First, analysis of the nasal microbiota of farm piglets sampled in this study, as well as various publicly available data sets, revealed that gut-microbiota associated taxa indeed constitute a substantial fraction of the pig nasal microbiota that is highly variable across individual animals. Second, comparison of herd-matched nasal and rectal samples at amplicon sequencing variant (ASV) level showed that these taxa are largely shared in the nasal and rectal microbiota, suggesting a common origin driven presumably by the transfer of fecal matter. Third, surgical sampling of the inner nasal tract showed that gut-microbiota associated taxa are found throughout the nasal cavity, indicating that these taxa do not stem from contaminations introduced during sampling with conventional nasal swabs. Finally, analysis of cDNA from the 16S rRNA gene in these nasal samples indicated that gut-microbiota associated taxa are indeed active in the pig nasal cavity. This study shows that gut-microbiota associated taxa are not only present, but also active, in the nasal cavity of domestic pigs, and paves the way for future efforts to elucidate the function of these taxa within the nasal microbiota.

Short cell cycle duration is a phenotype of human epidermal stem cells.

BACKGROUND: A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs). METHODS: We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing. RESULTS: We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC. CONCLUSIONS: Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

Global coordination of metabolic pathways in Escherichia coli by active and passive regulation.

Microorganisms adjust metabolic activity to cope with diverse environments. While many studies have provided insights into how individual pathways are regulated, the mechanisms that give rise to coordinated metabolic responses are poorly understood. Here, we identify the regulatory mechanisms that coordinate catabolism and anabolism in Escherichia coli. Integrating protein, metabolite, and flux changes in genetically implemented catabolic or anabolic limitations, we show that combined global and local mechanisms coordinate the response to metabolic limitations. To allocate proteomic resources between catabolism and anabolism, E. coli uses a simple global gene regulatory program. Surprisingly, this program is largely implemented by a single transcription factor, Crp, which directly activates the expression of catabolic enzymes and indirectly reduces the expression of anabolic enzymes by passively sequestering cellular resources needed for their synthesis. However, metabolic fluxes are not controlled by this regulatory program alone; instead, fluxes are adjusted mostly through passive changes in the local metabolite concentrations. These mechanisms constitute a simple but effective global regulatory program that coarsely partitions resources between different parts of metabolism while ensuring robust coordination of individual metabolic reactions.

Stress-induced growth rate reduction restricts metabolic resource utilization to modulate osmo-adaptation time.

A near-constant feature of stress responses is a downregulation or arrest of the cell cycle, resulting in transient growth slowdown. To investigate the role of growth slowdown in the hyperosmotic shock response of S. cerevisiae, we perturbed the G1/S checkpoint protein Sic1 to enable osmo-stress response activation with diminished growth slowdown. We document that in this mutant, adaptation to stress is accelerated rather than delayed. This accelerated recovery of the mutant proceeds by liquidation of internal glycogen stores, which are then shunted into the osmo-shock response. Therefore, osmo-adaptation in wild-type cells is delayed because growth slowdown prevents full accessibility to cellular glycogen stores. However, faster adaptation comes at the cost of acute sensitivity to subsequent osmo-stresses. We suggest that stress-induced growth slowdown acts as an arbiter to regulate the resources devoted to osmo-shock, balancing short-term adaptation with long-term robustness.

Systematic alteration of in vitro metabolic environments reveals empirical growth relationships in cancer cell phenotypes.

Cancer cells, like microbes, live in complex metabolic environments. Recent evidence suggests that microbial behavior across metabolic environments is well described by simple empirical growth relationships, or growth laws. Do such empirical growth relationships also exist in cancer cells? To test this question, we develop a high-throughput approach to extract quantitative measurements of cancer cell behaviors in systematically altered metabolic environments. Using this approach, we examine relationships between growth and three frequently studied cancer phenotypes: drug-treatment survival, cell migration, and lactate overflow. Drug-treatment survival follows simple linear growth relationships, which differ quantitatively between chemotherapeutics and EGFR inhibition. Cell migration follows a weak grow-and-go growth relationship, with substantial deviation in some environments. Finally, lactate overflow is mostly decoupled from growth rate and is instead determined by the cells' ability to maintain high sugar uptake rates. Altogether, this work provides a quantitative approach for formulating empirical growth laws of cancer.

Loss of TET2 Affects Proliferation and Drug Sensitivity through Altered Dynamics of Cell-State Transitions.

A persistent puzzle in cancer biology is how mutations, which neither alter growth signaling pathways nor directly interfere with drug mechanism, can still recur and persist in tumors. One example is the mutation of the DNA demethylase tet methylcytosine dioxygenase 2 (TET2) in acute myeloid leukemias (AMLs) that frequently persists from diagnosis through remission and relapse, but whose fitness advantage in chemotherapy is unclear. Here, we use isogenic human AML cell lines to show that TET2 loss of function alters the dynamics of transitions between differentiated and stem-like states. A conceptual mathematical model and experimental validation suggest that these altered cell-state dynamics can benefit the cell population by slowing population decay during drug treatment and lowering the number of survivor cells needed to re-establish the initial population. These studies shed light on the functional and phenotypic effects of a TET2 mutation in AML and illustrate how a single gene mutation can alter a cells' phenotypic plasticity. A record of this paper's transparent peer review process is included in the Supplemental Information.

Regulation underlying hierarchical and simultaneous utilization of carbon substrates by flux sensors in Escherichia coli.

Many microorganisms exhibit nutrient preferences, exemplified by the 'hierarchical' consumption of certain carbon substrates. Here, we systematically investigate under which physiological conditions hierarchical substrate utilization occurs and its mechanisms of implementation. We show utilization hierarchy of Escherichia coli to be ordered by the carbon-uptake flux rather than the identity of the substrates. A detailed study of glycerol uptake finds that it is fully suppressed if the uptake flux of another glycolytic substrate exceeds a threshold, which is set to the influx obtained when grown on glycerol alone. Below this threshold, limited glycerol uptake is 'supplemented' such that the total carbon uptake is maintained at the threshold. This behaviour results from total-flux feedback mediated by cAMP-Crp signalling but also requires inhibition by the regulator fructose 1,6-bisphosphate, which senses the upper-glycolytic flux and ensures that glycerol uptake defers to other glycolytic substrates but not to gluconeogenic ones. A quantitative model reproduces all of the observed utilization patterns, including those of key mutants. The proposed mechanism relies on the differential regulation of uptake enzymes and requires a specific operon organization. This organization is found to be conserved across related species for several uptake systems, suggesting the deployment of similar mechanisms for hierarchical substrate utilization by a spectrum of microorganisms.

Reserve Flux Capacity in the Pentose Phosphate Pathway Enables Escherichia coli's Rapid Response to Oxidative Stress.

To counteract oxidative stress and reactive oxygen species (ROS), bacteria evolved various mechanisms, primarily reducing ROS through antioxidant systems that utilize cofactor NADPH. Cells must stabilize NADPH levels by increasing flux through replenishing metabolic pathways like pentose phosphate (PP) pathway. Here, we investigate the mechanism enabling the rapid increase in NADPH supply by exposing Escherichia coli to hydrogen peroxide and quantifying the immediate metabolite dynamics. To systematically infer active regulatory interactions governing this response, we evaluated ensembles of kinetic models of glycolysis and PP pathway, each with different regulation mechanisms. Besides the known inactivation of glyceraldehyde 3-phosphate dehydrogenase by ROS, we reveal the important allosteric inhibition of the first PP pathway enzyme by NADPH. This NADPH feedback inhibition maintains a below maximum-capacity PP pathway flux under non-stress conditions. Relieving this inhibition instantly increases PP pathway flux upon oxidative stress. We demonstrate that reducing cells' capacity to rapidly reroute their flux through the PP pathway increases their oxidative stress sensitivity.

A Map of Protein-Metabolite Interactions Reveals Principles of Chemical Communication.

Metabolite-protein interactions control a variety of cellular processes, thereby playing a major role in maintaining cellular homeostasis. Metabolites comprise the largest fraction of molecules in cells, but our knowledge of the metabolite-protein interactome lags behind our understanding of protein-protein or protein-DNA interactomes. Here, we present a chemoproteomic workflow for the systematic identification of metabolite-protein interactions directly in their native environment. The approach identified a network of known and novel interactions and binding sites in Escherichia coli, and we demonstrated the functional relevance of a number of newly identified interactions. Our data enabled identification of new enzyme-substrate relationships and cases of metabolite-induced remodeling of protein complexes. Our metabolite-protein interactome consists of 1,678 interactions and 7,345 putative binding sites. Our data reveal functional and structural principles of chemical communication, shed light on the prevalence and mechanisms of enzyme promiscuity, and enable extraction of quantitative parameters of metabolite binding on a proteome-wide scale.

Drug persistence - from antibiotics to cancer therapies.

Drug-insensitive tumor subpopulations remain a significant barrier to effective cancer treatment. Recent works suggest that within isogenic drug-sensitive cancer populations, subsets of cells can enter a 'persister' state allowing them to survive prolonged drug treatment. Such persisters are well-described in antibiotic-treated bacterial populations. In this review, we compare mechanisms of drug persistence in bacteria and cancer. Both bacterial and cancer persisters are associated with slow-growing phenotypes, are metabolically distinct from non-persisters, and depend on the activation of specific regulatory programs. Moreover, evidence suggests that bacterial and cancer persisters are an important reservoir for the emergence of drug-resistant mutants. The emerging parallels between persistence in bacteria and cancer can guide efforts to untangle mechanistic links between growth, metabolism, and cellular regulation, and reveal exploitable therapeutic vulnerabilities.

Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli.

Transcription networks consist of hundreds of transcription factors with thousands of often overlapping target genes. While we can reliably measure gene expression changes, we still understand relatively little why expression changes the way it does. How does a coordinated response emerge in such complex networks and how many input signals are necessary to achieve it? Here, we unravel the regulatory program of gene expression in Escherichia coli central carbon metabolism with more than 30 known transcription factors. Using a library of fluorescent transcriptional reporters, we comprehensively quantify the activity of central metabolic promoters in 26 environmental conditions. The expression patterns were dominated by growth rate-dependent global regulation for most central metabolic promoters in concert with highly condition-specific activation for only few promoters. Using an approximate mathematical description of promoter activity, we dissect the contribution of global and specific transcriptional regulation. About 70% of the total variance in promoter activity across conditions was explained by global transcriptional regulation. Correlating the remaining specific transcriptional regulation of each promoter with the cell's metabolome response across the same conditions identified potential regulatory metabolites. Remarkably, cyclic AMP, fructose-1,6-bisphosphate, and fructose-1-phosphate alone explained most of the specific transcriptional regulation through their interaction with the two major transcription factors Crp and Cra. Thus, a surprisingly simple regulatory program that relies on global transcriptional regulation and input from few intracellular metabolites appears to be sufficient to coordinate E. coli central metabolism and explain about 90% of the experimentally observed transcription changes in 100 genes.

Distinct transcriptional regulation of the two Escherichia coli transhydrogenases PntAB and UdhA.

Transhydrogenases catalyse interconversion of the redox cofactors NADH and NADPH, thereby conveying metabolic flexibility to balance catabolic NADPH formation with anabolic or stress-based consumption of NADPH. Escherichia coli is one of the very few microbes that possesses two isoforms: the membrane-bound, proton-translocating transhydrogenase PntAB and the cytosolic, energy-independent transhydrogenase UdhA. Despite their physiological relevance, we have only fragmented information on their regulation and the signals coordinating their counteracting activities. Here we investigated PntAB and UdhA regulation by studying transcriptional responses to environmental and genetic perturbations. By testing pntAB and udhA GFP reporter constructs in the background of WT E. coli and 62 transcription factor mutants during growth on different carbon sources, we show distinct transcriptional regulation of the two transhydrogenase promoters. Surprisingly, transhydrogenase regulation was independent of the actual catabolic overproduction or underproduction of NADPH but responded to nutrient levels and growth rate in a fashion that matches the cellular need for the redox cofactors NADPH and/or NADH. Specifically, the identified transcription factors Lrp, ArgP and Crp link transhydrogenase expression to particular amino acids and intracellular concentrations of cAMP. The overall identified set of regulators establishes a primarily biosynthetic role for PntAB and link UdhA to respiration.

Systematic Identification of Protein-Metabolite Interactions in Complex Metabolite Mixtures by Ligand-Detected Nuclear Magnetic Resonance Spectroscopy.

Protein-metabolite interactions play a vital role in the regulation of numerous cellular processes. Consequently, identifying such interactions is a key prerequisite for understanding cellular regulation. However, the noncovalent nature of the binding between proteins and metabolites has so far hampered the development of methods for systematically mapping protein-metabolite interactions. The few available, largely mass spectrometry-based, approaches are restricted to specific metabolite classes, such as lipids. In this study, we address this issue and show the potential of ligand-detected nuclear magnetic resonance (NMR) spectroscopy, which is routinely used in drug development, to systematically identify protein-metabolite interactions. As a proof of concept, we selected four well-characterized bacterial and mammalian proteins (AroG, Eno, PfkA, and bovine serum albumin) and identified metabolite binders in complex mixes of up to 33 metabolites. Ligand-detected NMR captured all of the reported protein-metabolite interactions, spanning a full range of physiologically relevant Kd values (low micromolar to low millimolar). We also detected a number of novel interactions, such as promiscuous binding of the negatively charged metabolites citrate, AMP, and ATP, as well as binding of aromatic amino acids to AroG protein. Using in vitro enzyme activity assays, we assessed the functional relevance of these novel interactions in the case of AroG and show that l-tryptophan, l-tyrosine, and l-histidine act as novel inhibitors of AroG activity. Thus, we conclude that ligand-detected NMR is suitable for the systematic identification of functionally relevant protein-metabolite interactions.

The quantitative and condition-dependent Escherichia coli proteome.

Measuring precise concentrations of proteins can provide insights into biological processes. Here we use efficient protein extraction and sample fractionation, as well as state-of-the-art quantitative mass spectrometry techniques to generate a comprehensive, condition-dependent protein-abundance map for Escherichia coli. We measure cellular protein concentrations for 55% of predicted E. coli genes (>2,300 proteins) under 22 different experimental conditions and identify methylation and N-terminal protein acetylations previously not known to be prevalent in bacteria. We uncover system-wide proteome allocation, expression regulation and post-translational adaptations. These data provide a valuable resource for the systems biology and broader E. coli research communities.

Posttranslational regulation of microbial metabolism.

Fluxes in microbial metabolism are controlled by various regulatory layers that alter abundance or activity of metabolic enzymes. Recent studies suggest a division of labor between these layers: transcriptional regulation mostly controls the allocation of protein resources, passive flux regulation by enzyme saturation and thermodynamics allows rapid responses at the expense of higher protein cost, and posttranslational regulation is utilized by cells to directly take control of metabolic decisions. We present recent advances in elucidating the role of these regulatory layers, focusing on posttranslational modifications and allosteric interactions. As the systematic mapping of posttranslational regulatory events has now become possible, the next challenge is to identify those regulatory events that are functionally relevant under a given condition.

Pseudo-transition Analysis Identifies the Key Regulators of Dynamic Metabolic Adaptations from Steady-State Data.

Hundreds of molecular-level changes within central metabolism allow a cell to adapt to the changing environment. A primary challenge in cell physiology is to identify which of these molecular-level changes are active regulatory events. Here, we introduce pseudo-transition analysis, an approach that uses multiple steady-state observations of (13)C-resolved fluxes, metabolites, and transcripts to infer which regulatory events drive metabolic adaptations following environmental transitions. Pseudo-transition analysis recapitulates known biology and identifies an unexpectedly sparse, transition-dependent regulatory landscape: typically a handful of regulatory events drive adaptation between carbon sources, with transcription mainly regulating TCA cycle flux and reactants regulating EMP pathway flux. We verify these observations using time-resolved measurements of the diauxic shift, demonstrating that some dynamic transitions can be approximated as monotonic shifts between steady-state extremes. Overall, we show that pseudo-transition analysis can explore the vast regulatory landscape of dynamic transitions using relatively few steady-state data, thereby guiding time-consuming, hypothesis-driven molecular validations.

Coordination of microbial metabolism.

Beyond fuelling cellular activities with building blocks and energy, metabolism also integrates environmental conditions into intracellular signals. The underlying regulatory network is complex and multifaceted: it ranges from slow interactions, such as changing gene expression, to rapid ones, such as the modulation of protein activity via post-translational modification or the allosteric binding of small molecules. In this Review, we outline the coordination of common metabolic tasks, including nutrient uptake, central metabolism, the generation of energy, the supply of amino acids and protein synthesis. Increasingly, a set of key metabolites is recognized to control individual regulatory circuits, which carry out specific functions of information input and regulatory output. Such a modular view of microbial metabolism facilitates an intuitive understanding of the molecular mechanisms that underlie cellular decision making.

Dissecting specific and global transcriptional regulation of bacterial gene expression.

Gene expression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional--but often neglected--layer of complexity in gene expression. Here, we develop an experimental-computational approach to dissect specific and global regulation in the bacterium Escherichia coli. By using fluorescent promoter reporters, we show that global regulation is growth rate dependent not only during steady state but also during dynamic changes in growth rate and can be quantified through two promoter-specific parameters. By applying our approach to arginine biosynthesis, we obtain a quantitative understanding of both specific and global regulation that allows accurate prediction of the temporal response to simultaneous perturbations in arginine availability and growth rate. We thereby uncover two principles of joint regulation: (i) specific regulation by repression dominates the transcriptional response during metabolic steady states, largely repressing the biosynthesis genes even when biosynthesis is required and (ii) global regulation sets the maximum promoter activity that is exploited during the transition between steady states.

Somewhat in control--the role of transcription in regulating microbial metabolic fluxes.

The most common way for microbes to control their metabolism is by controlling enzyme levels through transcriptional regulation. Yet recent studies have shown that in many cases, perturbations to the transcriptional regulatory network do not result in altered metabolic phenotypes on the level of the flux distribution. We suggest that this may be a consequence of cells protecting their metabolism against stochastic fluctuations in expression as well as enabling a fast response for those fluxes that may need to be changed quickly. Furthermore, it is impossible for a regulatory program to guarantee optimal expression levels in all conditions. Several studies have found examples of demonstrably suboptimal regulation of gene expression, and improvements to the regulatory network have been investigated in laboratory evolution experiments.

Systematic identification of allosteric protein-metabolite interactions that control enzyme activity in vivo.

Recent data suggest that the majority of proteins bind specific metabolites and that such interactions are relevant to metabolic and gene regulation. However, there are no methods to systematically identify functional allosteric protein-metabolite interactions. Here we present an experimental and computational approach for using dynamic metabolite data to discover allosteric regulation that is relevant in vivo. By switching the culture conditions of Escherichia coli every 30 s between medium containing either pyruvate or (13)C-labeled fructose or glucose, we measured the reversal of flux through glycolysis pathways and observed rapid changes in metabolite concentration. We fit these data to a kinetic model of glycolysis and systematically tested the consequences of 126 putative allosteric interactions on metabolite dynamics. We identified allosteric interactions that govern the reversible switch between gluconeogenesis and glycolysis, including one by which pyruvate activates fructose-1,6-bisphosphatase. Thus, from large sets of putative allosteric interactions, our approach can identify the most likely ones and provide hypotheses about their function.