iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of AYE.

has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions.

High-Level dCas9 Expression Induces Abnormal Cell Morphology in Escherichia coli.

Along with functional advances in the use of CRISPR/Cas9 for genome editing, endonuclease-deficient Cas9 (dCas9) has provided a versatile molecular tool for exploring gene functions. In principle, differences in cell phenotypes that result from the RNA-guided modulation of transcription levels by dCas9 are critical for inferring with gene function; however, the effect of intracellular dCas9 expression on bacterial morphology has not been systematically elucidated. Here, we observed unexpected morphological changes in Escherichia coli mediated by dCas9, which were then characterized using RNA sequencing (RNA-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq).

Systems biology as an emerging paradigm in transfusion medicine.

Blood transfusions are an important part of modern medicine, delivering approximately 85 million blood units to patients annually. Recently, the field of transfusion medicine has started to benefit from the "omic" data revolution and corresponding systems biology analytics. The red blood cell is the simplest human cell, making it an accessible starting point for the application of systems biology approaches.

Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions.

Background: The efficacy of antibiotics against M. tuberculosis has been shown to be influenced by experimental media conditions. Investigations of M.

Recon3D enables a three-dimensional view of gene variation in human metabolism.

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs.

ssbio: a Python framework for structural systems biology.

Summary: Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows.

Quantitative -omic data empowers bottom-up systems biology.

The large-scale generation of '-omic' data holds the potential to increase and deepen our understanding of biological phenomena, but the ability to synthesize information and extract knowledge from these data sets still represents a significant challenge. Bottom-up systems biology overcomes this hurdle through the integration of disparate -omic data types, and absolutely quantified experimental measurements allow for direct integration into quantitative, mechanistic models. The human red blood cell has served as a starting point for the application of systems biology approaches and has been the focus of a recent burst of generated quantitative metabolomics and proteomics data.

Genome-scale analysis of Methicillin-resistant Staphylococcus aureus USA300 reveals a tradeoff between pathogenesis and drug resistance.

Staphylococcus aureus infection is a rising public health care threat. S. aureus is believed to have elaborate regulatory networks that orchestrate its virulence.

Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP.

Two major transcriptional regulators of carbon metabolism in bacteria are Cra and CRP. CRP is considered to be the main mediator of catabolite repression. Unlike for CRP, in vivo DNA binding information of Cra is scarce.

Modeling the multi-scale mechanisms of macromolecular resource allocation.

As microbes face changing environments, they dynamically allocate macromolecular resources to produce a particular phenotypic state. Broad 'omics' data sets have revealed several interesting phenomena regarding how the proteome is allocated under differing conditions, but the functional consequences of these states and how they are achieved remain open questions. Various types of multi-scale mathematical models have been used to elucidate the genetic basis for systems-level adaptations.

Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting.

Several antimalarial drugs exist, but differences between life cycle stages among malaria species pose challenges for developing more effective therapies. To understand the diversity among stages and species, we reconstructed genome-scale metabolic models (GeMMs) of metabolism for five life cycle stages and five species of Plasmodium spanning the blood, transmission, and mosquito stages. The stage-specific models of Plasmodium falciparum uncovered stage-dependent changes in central carbon metabolism and predicted potential targets that could affect several life cycle stages.

Metabolic Models of Protein Allocation Call for the Kinetome.

The flux of metabolites in the living cell depend on enzyme activities. Recently, many metabolic phenotypes have been explained by computer models that incorporate enzyme activity data. To move further, the scientific community needs to measure the kinetics of all enzymes in a systematic way.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism.

Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks.

Dissecting the genetic and metabolic mechanisms of adaptation to the knockout of a major metabolic enzyme in .

Unraveling the mechanisms of microbial adaptive evolution following genetic or environmental challenges is of fundamental interest in biological science and engineering. When the challenge is the loss of a metabolic enzyme, adaptive responses can also shed significant insight into metabolic robustness, regulation, and areas of kinetic limitation. In this study, whole-genome sequencing and high-resolution C-metabolic flux analysis were performed on 10 adaptively evolved knockouts of catalyzes the first reaction in glycolysis, and its loss results in major physiological and carbon catabolism pathway changes, including an 80% reduction in growth rate.

Proceedings of the Food and Drug Administration's public workshop on new red blood cell product regulatory science 2016.

The US Food and Drug Administration (FDA) held a workshop on red blood cell (RBC) product regulatory science on October 6 and 7, 2016, at the Natcher Conference Center on the National Institutes of Health (NIH) Campus in Bethesda, Maryland. The workshop was supported by the National Heart, Lung, and Blood Institute, NIH; the Department of Defense; the Office of the Assistant Secretary for Health, Department of Health and Human Services; and the Center for Biologics Evaluation and Research, FDA. The workshop reviewed the status and scientific basis of the current regulatory framework and the available scientific tools to expand it to evaluate innovative and future RBC transfusion products.

Antibiotic-Induced Changes to the Host Metabolic Environment Inhibit Drug Efficacy and Alter Immune Function.

Bactericidal antibiotics alter microbial metabolism as part of their lethality and can damage mitochondria in mammalian cells. In addition, antibiotic susceptibility is sensitive to extracellular metabolites, but it remains unknown whether metabolites present at an infection site can affect either treatment efficacy or immune function. Here, we quantify local metabolic changes in the host microenvironment following antibiotic treatment for a peritoneal Escherichia coli infection.

Thermosensitivity of growth is determined by chaperone-mediated proteome reallocation.

Maintenance of a properly folded proteome is critical for bacterial survival at notably different growth temperatures. Understanding the molecular basis of thermoadaptation has progressed in two main directions, the sequence and structural basis of protein thermostability and the mechanistic principles of protein quality control assisted by chaperones. Yet we do not fully understand how structural integrity of the entire proteome is maintained under stress and how it affects cellular fitness.

Quantitative time-course metabolomics in human red blood cells reveal the temperature dependence of human metabolic networks.

The temperature dependence of biological processes has been studied at the levels of individual biochemical reactions and organism physiology ( basal metabolic rates) but has not been examined at the metabolic network level. Here, we used a systems biology approach to characterize the temperature dependence of the human red blood cell (RBC) metabolic network between 4 and 37 °C through absolutely quantified exo- and endometabolomics data. We used an Arrhenius-type model () to describe how the rate of a biochemical process changes with every 10 °C change in temperature.

A Padawan Programmer's Guide to Developing Software Libraries.

With the rapid adoption of computational tools in the life sciences, scientists are taking on the challenge of developing their own software libraries and releasing them for public use. This trend is being accelerated by popular technologies and platforms, such as GitHub, Jupyter, R/Shiny, that make it easier to develop scientific software and by open-source licenses that make it easier to release software. But how do you build a software library that people will use? And what characteristics do the best libraries have that make them enduringly popular? Here, we provide a reference guide, based on our own experiences, for developing software libraries along with real-world examples to help provide context for scientists who are learning about these concepts for the first time.

Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring.

Adaptive laboratory evolution (ALE) is a widely-used method for improving the fitness of microorganisms in selected environmental conditions. It has been applied previously to Escherichia coli K-12 MG1655 during aerobic exponential growth on glucose minimal media, a frequently used model organism and growth condition, to probe the limits of E. coli growth rate and gain insights into fast growth phenotypes.

Global transcriptional regulatory network for robustly connects gene expression to transcription factor activities.

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the TRN-probably the best characterized TRN-several questions remain. Here, we address three questions: () How complete is our knowledge of the TRN; () how well can we predict gene expression using this TRN; and () how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes.

Mannose and fructose metabolism in red blood cells during cold storage in SAGM.

Background: Alternate sugar metabolism during red blood cell (RBC) storage is not well understood. Here we report fructose and mannose metabolism in RBCs during cold storage in SAGM and the impact that these monosaccharides have on metabolic biomarkers of RBC storage lesion.

Study Design And Methods: RBCs were stored in SAGM containing uniformly labeled C-fructose or C-mannose at 9 or 18 mmol/L concentration for 25 days.

Revealing genome-scale transcriptional regulatory landscape of OmpR highlights its expanded regulatory roles under osmotic stress in Escherichia coli K-12 MG1655.

A transcription factor (TF), OmpR, plays a critical role in transcriptional regulation of the osmotic stress response in bacteria. Here, we reveal a genome-scale OmpR regulon in Escherichia coli K-12 MG1655. Integrative data analysis reveals that a total of 37 genes in 24 transcription units (TUs) belong to OmpR regulon.

Laboratory Evolution to Alternating Substrate Environments Yields Distinct Phenotypic and Genetic Adaptive Strategies.

Adaptive laboratory evolution (ALE) experiments are often designed to maintain a static culturing environment to minimize confounding variables that could influence the adaptive process, but dynamic nutrient conditions occur frequently in natural and bioprocessing settings. To study the nature of carbon substrate fitness tradeoffs, we evolved batch cultures of via serial propagation into tubes alternating between glucose and either xylose, glycerol, or acetate. Genome sequencing of evolved cultures revealed several genetic changes preferentially selected for under dynamic conditions and different adaptation strategies depending on the substrates being switched between; in some environments, a persistent "generalist" strain developed, while in another, two "specialist" subpopulations arose that alternated dominance.