Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.

Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machine learning can successfully predict catalytic turnover numbers in Escherichia coli based on integrated data on enzyme biochemistry, protein structure, and network context. We identify a diverse set of features that are consistently predictive for both in vivo and in vitro enzyme turnover rates, revealing novel protein structural correlates of catalytic turnover. We use our predictions to parameterize two mechanistic genome-scale modelling frameworks for proteome-limited metabolism, leading to significantly higher accuracy in the prediction of quantitative proteome data than previous approaches. The presented machine learning models thus provide a valuable tool for understanding metabolism and the proteome at the genome scale, and elucidate structural, biochemical, and network properties that underlie enzyme kinetics

Factors Associated With the Appropriate Use of Ultra-Broad Spectrum Antibiotics, Meropenem, for Suspected Healthcare-Associated Pneumonia

ABSTRACT: Pneumonia is a common disease-causing hospitalization. When a healthcare-associated infection is suspected, antibiotics that provide coverage for multi-drug resistant (MDR) or extended-spectrum beta-lactamase (ESBL) bacteria are frequently prescribed. Limited data is available for guidance on using meropenem as a first-line empiric antimicrobial in hospitalized patients with risk factors for MDR/ESBL bacterial infections. This was a single-center, retrospective study designed and conducted to identify factors associated with positive cultures for MDR/ESBL pathogens in hospitalized patients with suspected healthcare-associated pneumonia.Of the 246 patients, 103 patients (41%) received meropenem. Among patients prescribed meropenem, MDR/ESBL pathogens were detected in only 20 patients (13%). Patients admitted from a skilled nursing facility/long-term acute care (SNF/LTAC) or with a history of a positive culture for MDR/ESBL pathogens were significantly associated with positive cultures of MDR/ESBL pathogens during the hospitalization (odds ratio [95% confidence intervals], 31.40 [5.20-189.6] in SNF/LTAC and 18.50 [2.98-115.1] in history of culture-positive MDR/ESBL pathogen). There was no significant difference in mortality between the 3 antibiotic groups.Admission from a SNF/LTAC or having a history of cultures positive for MDR/ESBL pathogens were significantly associated with a positive culture for MDR/ESBL pathogens during the subsequent admission. We did not detect significant association between meropenem use as a first-line drug and morbidity and mortality for patients admitted to the hospital with suspected healthcare-associated pneumonia, and further prospective studies with larger sample size are needed to confirm our findings

Observation of Skewed Electromagnetic Wakefields in an Asymmetric Structure Driven by Flat Electron Bunches

Relativistic charged-particle beams which generate intense longitudinal fields in accelerating structures also inherently couple to transverse modes. The effects of this coupling may lead to beam break-up instability, and thus must be countered to preserve beam quality in applications such as linear colliders. Beams with highly asymmetric transverse sizes (flat-beams) have been shown to suppress the initial instability in slab-symmetric structures. However, as the coupling to transverse modes remains, this solution serves only to delay instability. In order to understand the hazards of transverse coupling in such a case, we describe here an experiment characterizing the transverse effects on a flat-beam, traversing near a planar dielectric lined structure. The measurements reveal the emergence of a previously unobserved skew-quadrupole-like interaction when the beam is canted transversely, which is not present when the flat-beam travels parallel to the dielectric surface. We deploy a multipole field fitting algorithm to reconstruct the projected transverse wakefields from the data. We generate the effective kick vector map using a simple two-particle theoretical model, with particle-in-cell simulations used to provide further insight for realistic particle distributions.Comment: Six pages, seven figures. Submitted to Physical Revie

Extracting density-density correlations from in situ images of atomic quantum gases

We present a complete recipe to extract the density-density correlations and the static structure factor of a two-dimensional (2D) atomic quantum gas from in situ imaging. Using images of non-interacting thermal gases, we characterize and remove the systematic contributions of imaging aberrations to the measured density-density correlations of atomic samples. We determine the static structure factor and report results on weakly interacting 2D Bose gases, as well as strongly interacting gases in a 2D optical lattice. In the strongly interacting regime, we observe a strong suppression of the static structure factor at long wavelengths.Comment: 15 pages, 5 figure

Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion

Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production

Microbial laboratory evolution in the era of genome-scale science

Advances in DNA sequencing, high-throughput technologies, and genetic manipulation systems have enabled empirical studies of the molecular and genomic bases of adaptive evolution. This review discusses key insights learned from direct observation of the evolution process

Enhancing CHO cell productivity through a novel dual selection system using Aspg and Gs in glutamine free medium

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