Independent component analysis reveals 49 independently modulated gene sets within the global transcriptional regulatory architecture of multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii causes severe infections in humans, resists multiple antibiotics, and survives in stressful environmental conditions due to modulations of its complex transcriptional regulatory network (TRN). Unfortunately, our global understanding of the TRN in this emerging opportunistic pathogen is limited. Here, we apply independent component analysis, an unsupervised machine learning method, to a compendium of 139 RNA-seq data sets of three multidrug-resistant A. baumannii international clonal complex I strains (AB5075, AYE, and AB0057). This analysis allows us to define 49 independently modulated gene sets, which we call iModulons. Analysis of the identified A. baumannii iModulons reveals validating parallels to previously defined biological operons/regulons and provides a framework for defining unknown regulons. By utilizing the iModulons, we uncover potential mechanisms for a RpoS-independent general stress response, define global stress-virulence trade-offs, and identify conditions that may induce plasmid-borne multidrug resistance. The iModulons provide a model of the TRN that emphasizes the importance of transcriptional regulation of virulence phenotypes in A. baumannii. Furthermore, they suggest the possibility of future interventions to guide gene expression toward diminished pathogenic potential.IMPORTANCEThe rise in hospital outbreaks of multidrug-resistant Acinetobacter baumannii infections underscores the urgent need for alternatives to traditional broad-spectrum antibiotic therapies. The success of A. baumannii as a significant nosocomial pathogen is largely attributed to its ability to resist antibiotics and survive environmental stressors. However, there is limited literature available on the global, complex regulatory circuitry that shapes these phenotypes. Computational tools that can assist in the elucidation of A. baumannii's transcriptional regulatory network architecture can provide much-needed context for a comprehensive understanding of pathogenesis and virulence, as well as for the development of targeted therapies that modulate these pathways.

In ovo administration of the Marek's disease vaccine in conjunction with 25-hydroxyvitamin D3 and its subsequent effects on the performance and immunity-related characteristics of Ross 708 broiler hatchlings1,2,3

The combined effects of the in ovo injection of commercial Marek's disease vaccine (MDV) and various levels of 25-hydroxyvitamin D3 (25OHD3) on the hatch variables, immunological measurements, and gene expression of Ross 708 hatchling broilers were investigated. A total of 5 in ovo injection treatments that were applied at 18 d of incubation (doi) included: 1) noninjected (control); or a 50 μL solution volume of 2) MDV alone; or MDV combined with 3) 0.6 μg of 25OHD3; 4) 1.2 μg of 25OHD3; or 5) 2.4 μg of 25OHD3. At hatch, hatchability of set and live embryonated eggs, hatchling body weight, hatch residue analysis, serum IgY and alpha-1 acid glycoprotein (AGP) concentrations, and the expression of genes related to immunity (INFα, INFβ, INFγ, TLR-3, and TLR-21) and vitamin D3 activity (1 α-hydroxylase, 24 hydroxylase, and vitamin D receptor) were determined. No significant treatment differences were observed for hatchability of set and live embryonated eggs, or for serum IgY and AGP concentrations. However, hatchling body weight was higher when MDV was combined with either 1.2 or 2.4 μg of 25OHD3 than when MDV was provided alone or in combination with 0.6 μg of 25OHD3. Also, in comparison to the noninjected treatment group, the expression of the genes for 1 α-hydroxylase and 24 hydroxylase was improved when MDV was combined with either 1.2 or 2.4 μg of 25OHD3. Lastly, expression of the genes linked to viral detection (TLR-3) and antibody production (INF-β) was increased in those treatments that contained any level of 25OHD3. These results indicate that in comparison to controls, the effects of MDV were observed to be greater on hatchling BW and splenic gene expression when it was administered in combination with the 1.2 or 2.4 μg doses of 25OHD3. Further research is needed to determine the posthatch effects of the administration of various levels of 25OHD3 in combination with MDV.

First Measurement of the Nuclear-Recoil Ionization Yield in Silicon at 100 eV

We measured the nuclear-recoil ionization yield in silicon with a cryogenic phonon-sensitive gram-scale detector. Neutrons from a monoenergetic beam scatter off of the silicon nuclei at angles corresponding to energy depositions from 4 keV down to 100 eV, the lowest energy probed so far. The results show no sign of an ionization production threshold above 100 eV. These results call for further investigation of the ionization yield theory and a comprehensive determination of the detector response function at energies below the keV scale.

Elucidating the CodY regulon in Staphylococcus aureus USA300 substrains TCH1516 and LAC

CodY is a conserved broad-acting transcription factor that regulates the expression of genes related to amino acid metabolism and virulence in Gram-positive bacteria. Here, we performed the first in vivo determination of CodY target genes using a novel CodY monoclonal antibody in methicillin-resistant Staphylococcus aureus (MRSA) USA300. Our results showed (i) the same 135 CodY promoter binding sites regulating the 165 target genes identified in two closely related virulent S. aureus USA300 TCH1516 and LAC strains; (ii) the differential binding intensity for the same target genes under the same conditions was due to sequence differences in the same CodY-binding site in the two strains; (iii) a CodY regulon comprising 72 target genes that are differentially regulated relative to a CodY deletion strain, representing genes that are mainly involved in amino acid transport and metabolism, inorganic ion transport and metabolism, transcription and translation, and virulence, all based on transcriptomic data; and (iv) CodY systematically regulated central metabolic flux to generate branched-chain amino acids (BCAAs) by mapping the CodY regulon onto a genome-scale metabolic model of S. aureus. Our study performed the first system-level analysis of CodY in two closely related USA300 TCH1516 and LAC strains, revealing new insights into the similarities and differences of CodY regulatory roles between the closely related strains. IMPORTANCE With the increasing availability of whole-genome sequences for many strains within the same pathogenic species, a comparative analysis of key regulators is needed to understand how the different strains uniquely coordinate metabolism and expression of virulence. To successfully infect the human host, Staphylococcus aureus USA300 relies on the transcription factor CodY to reorganize metabolism and express virulence factors. While CodY is a known key transcription factor, its target genes are not characterized on a genome-wide basis. We performed a comparative analysis to describe the transcriptional regulation of CodY between two dominant USA300 strains. This study motivates the characterization of common pathogenic strains and an evaluation of the possibility of developing specialized treatments for major strains circulating in the population.

Elucidation of independently modulated genes in Streptococcus pyogenes reveals carbon sources that control its expression of hemolytic toxins

Streptococcus pyogenes can cause a wide variety of acute infections throughout the body of its human host. An underlying transcriptional regulatory network (TRN) is responsible for altering the physiological state of the bacterium to adapt to each unique host environment. Consequently, an in-depth understanding of the comprehensive dynamics of the S. pyogenes TRN could inform new therapeutic strategies. Here, we compiled 116 existing high-quality RNA sequencing data sets of invasive S. pyogenes serotype M1 and estimated the TRN structure in a top-down fashion by performing independent component analysis (ICA). The algorithm computed 42 independently modulated sets of genes (iModulons). Four iModulons contained the nga-ifs-slo virulence-related operon, which allowed us to identify carbon sources that control its expression. In particular, dextrin utilization upregulated the nga-ifs-slo operon by activation of two-component regulatory system CovRS-related iModulons, altering bacterial hemolytic activity compared to glucose or maltose utilization. Finally, we show that the iModulon-based TRN structure can be used to simplify the interpretation of noisy bacterial transcriptome data at the infection site.IMPORTANCES. pyogenes is a pre-eminent human bacterial pathogen that causes a wide variety of acute infections throughout the body of its host. Understanding the comprehensive dynamics of its TRN could inform new therapeutic strategies. Since at least 43 S. pyogenes transcriptional regulators are known, it is often difficult to interpret transcriptomic data from regulon annotations. This study shows the novel ICA-based framework to elucidate the underlying regulatory structure of S. pyogenes allows us to interpret the transcriptome profile using data-driven regulons (iModulons). Additionally, the observations of the iModulon architecture lead us to identify the multiple regulatory inputs governing the expression of a virulence-related operon. The iModulons identified in this study serve as a powerful guidepost to further our understanding of S. pyogenes TRN structure and dynamics.

Malnutrition among Cancer Patients in a Tertiary Care Centre: A Descriptive Cross-sectional Study

Introduction

Malnutrition is one of the most frequent disorders among cancer patients. It is seen in 50-90% of cancer patients. This high prevalence of malnutrition is very concerning as it is associated with reduced effective treatment, functional status, quality of life and survival. The aim of the study was to find out the prevalence of malnutrition among cancer patients in a tertiary care centre.

Methods

A descriptive cross-sectional study was conducted among 95 cancer patients in the Department of Clinical Oncology of a tertiary care centre from 25 January 2022 to 25 July 2022. Ethical approval was obtained from the Institutional Review Committee (Reference number: 1192/2078/79). Convenience sampling was done. Patients were screened using Patient-Generated Subjective Global Assessment for malnutrition. Point estimate and 95% Confidence Interval were calculated.

Results

Among 95 cancer patients, 22 (23.15%) (15.10-32.90, 95% Confidence Interval) were malnourished.

Conclusions

The prevalence of malnutrition was found to be lower than in other studies done in similar settings. Nutritional assessment and support should be an integral part of care for gastrointestinal cancer.

Keywords

malnourishment; nutritional deficiency; screening.

Immunomodulatory effect of different statin regimens on regulatory T-cells among patients with acute coronary syndrome: a systematic review and network meta-analysis of randomized clinical trials

Funding Acknowledgements

Type of funding sources: None.

Immunomodulatory effect of different statin regimens on regulatory T-cells  among patients with acute coronary syndrome: a systematic review  and network meta-analysis of randomized clinical trials

Introduction

In patients with acute coronary syndrome (ACS), studies suggest that statin therapy, besides its role in reducing the progression of atherosclerosis through its pharmacological effect, plays a pivotal role in controlling the pathogenesis of ACS through the anti-inflammatory effects of suppressor regulatory T cells (Tregs).

Purpose

We conducted a network meta-analysis (NMA) to determine the effects of low-dose conventional statin therapy (CST) (20 mg/day or less) and high-dose intensive statin therapy (IST) (40 mg/day or more) on the frequency of Tregs and their associated cytokines (IFN-γ, IL-10, TGF-β), compared to placebo.

Methods

The PubMed, Cochrane Library, and EMBASE databases were searched for randomized clinical trials (RCTs) to identify relevant articles published until June 2021. We pooled data extracted from the included studies using the standardized mean difference (SMD). A random-effects model was used to conduct this NMA. Heterogeneity was evaluated using Cochran's Q- and the I2-test. GRADE(Grading of Recommendations, Assessment, Development and Evaluations) was used to assess the study's quality. Data analysis was conducted using R software.

Results

A total of 505 patients were enrolled in the 5 RCTs. The NMA indicated a significant increase in Treg frequency in the CST group compared with the control group (SMD 1.77; 95% CI: 0.77 – 2.76; P-value = 0.0005) and a larger increase in the Treg frequency associated with the IST group compared with the control group (SMD 2.12; 95% CI: 1.15 – 3.10; P-value < 0.0001). However, there was significant heterogeneity and inconsistency among the included studies (τ2 = 0.6096; τ = 0.7808; I2 = 91.2% [80.5%; 96.0%]). When compared to the placebo, both CST and IST increased levels of secreted IL-10 (SMD 2.69; 95% CI: 2.07 – 3.31; P-value < 0.0001 and (SMD 2.14; 95% CI: 1.76 – 2.52; P-value < 0.0001), respectively. In comparison to the control group, CST was associated with increased levels of TGF-β (SMD 3.83; 95% CI: 0.63 – 7.0; P-value = 0.0189). This association was not seen in the IST group. IFN-γ levels decreased significantly in both the IST and CST groups (SMD -1.52; 95% CI: -1.94 – -1.10; P-value < 0.0001) and (SMD -2.34; 95% CI: -2.73 – -1.95; P-value < 0.0001) respectively.

Conclusions

Our study suggests that both high and low dose statin groups showed increased Treg frequency compared to the placebo group. IST showed larger benefits. Statin therapy also increased IL-10 and TGF-β cytokine levels and decreased IFN-γ levels. Therefore, statins have the potential to be the main treatment to reduce the incidence of cardiovascular events and improve cardiac function in patients with ACS through immunomodulatory effect on Treg.

Mathematical models to study the biology of pathogens and the infectious diseases they cause

Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.

Health Promoting Lifestyle during Covid-19 Pandemic among Residents of Gandaki Province, Nepal

Background Lifestyle is an important factor to individual's health and quality of life. Although, the emergence of Corona virus disease 2019 (COVID-19) has forced billions of people to change their lifestyle overnight. Objective To identify health promoting lifestyle during COVID-19 pandemic among the residents of Gandaki Province, Nepal. Method Descriptive cross sectional web based study was conducted among 386 respondents from Gandaki Province. Adults from 18 years and above, who could fill the form online were included using purposive and snowball sampling technique. Data were collected using Health Promoting Lifestyle Profile II (HPLP II) scale and analysed using descriptive (frequency, percentage, median) and inferential statistics (Mann Whitney U test and Kruskal Wallis test). Result Only 18.7% of the respondents had an excellent health promoting lifestyle followed by good health promoting lifestyle among 60.4%. Highest median score was observed in spiritual 27(10-36), and interpersonal relationship subscale 27(9-36). Whereas, the lowest was observed in physical activity 21(8-32) followed by stress management 24(10-32). Statistically significant difference was observed in age and perception of own health status with spirituality; gender, chronic illness and perception of own health status with interpersonal subscale and age, gender, marital status, occupation and perception of own health status with physical subscale. Conclusion The study concludes the need of health education and awareness to promote healthy lifestyle behaviours with a particular emphasis on indoor physical activities and stress management skills with specific consideration to female and elderly.

Optimal dimensionality selection for independent component analysis of transcriptomic data

Background

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question.

Methods

We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension.

Results

We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes.

Conclusions

OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04497-7.

Machine Learning Uncovers a Data-Driven Transcriptional Regulatory Network for the Crenarchaeal Thermoacidophile Sulfolobus acidocaldarius

Dynamic cellular responses to environmental constraints are coordinated by the transcriptional regulatory network (TRN), which modulates gene expression. This network controls most fundamental cellular responses, including metabolism, motility, and stress responses. Here, we apply independent component analysis, an unsupervised machine learning approach, to 95 high-quality Sulfolobus acidocaldarius RNA-seq datasets and extract 45 independently modulated gene sets, or iModulons. Together, these iModulons contain 755 genes (32% of the genes identified on the genome) and explain over 70% of the variance in the expression compendium. We show that five modules represent the effects of known transcriptional regulators, and hypothesize that most of the remaining modules represent the effects of uncharacterized regulators. Further analysis of these gene sets results in: (1) the prediction of a DNA export system composed of five uncharacterized genes, (2) expansion of the LysM regulon, and (3) evidence for an as-yet-undiscovered global regulon. Our approach allows for a mechanistic, systems-level elucidation of an extremophile's responses to biological perturbations, which could inform research on gene-regulator interactions and facilitate regulator discovery in S. acidocaldarius. We also provide the first global TRN for S. acidocaldarius. Collectively, these results provide a roadmap toward regulatory network discovery in archaea.

RiboRid: A low cost, advanced, and ultra-efficient method to remove ribosomal RNA for bacterial transcriptomics

RNA sequencing techniques have enabled the systematic elucidation of gene expression (RNA-Seq), transcription start sites (differential RNA-Seq), transcript 3′ ends (Term-Seq), and post-transcriptional processes (ribosome profiling). The main challenge of transcriptomic studies is to remove ribosomal RNAs (rRNAs), which comprise more than 90% of the total RNA in a cell. Here, we report a low-cost and robust bacterial rRNA depletion method, RiboRid, based on the enzymatic degradation of rRNA by thermostable RNase H. This method implemented experimental considerations to minimize nonspecific degradation of mRNA and is capable of depleting pre-rRNAs that often comprise a large portion of RNA, even after rRNA depletion. We demonstrated the highly efficient removal of rRNA up to a removal efficiency of 99.99% for various transcriptome studies, including RNA-Seq, Term-Seq, and ribosome profiling, with a cost of approximately $10 per sample. This method is expected to be a robust method for large-scale high-throughput bacterial transcriptomic studies.

Removal of ribosomal RNAs, a major constituent (over 90%) of cellular RNA is a critical experimental step for transcriptomic studies that deal with messenger RNAs. In this manuscript, we describe a robust method to subtract ribosomal RNA from various RNA samples. The method is based on the enzymatic degradation of target RNA by short complementary DNA and RNA:DNA duplex specific nuclease. The method comprises carefully designed experimental procedures to minimize experimental bias and unwanted removal of messenger RNAs. We validate the method on various types of transcriptomic studies for seven diverse bacterial species. This method successfully removed ribosomal RNA with over 99% of efficiency and it was comparable to commercial systems even for degraded RNA samples at a fraction of a cost.

Constraints on Lightly Ionizing Particles from CDMSlite

The Cryogenic Dark Matter Search low ionization threshold experiment (CDMSlite) achieved efficient detection of very small recoil energies in its germanium target, resulting in sensitivity to lightly ionizing particles (LIPs) in a previously unexplored region of charge, mass, and velocity parameter space. We report first direct-detection limits calculated using the optimum interval method on the vertical intensity of cosmogenically produced LIPs with an electric charge smaller than e/(3×10^{5}), as well as the strongest limits for charge ≤e/160, with a minimum vertical intensity of 1.36×10^{-7}  cm^{-2} s^{-1} sr^{-1} at charge e/160. These results apply over a wide range of LIP masses (5  MeV/c^{2} to 100  TeV/c^{2}) and cover a wide range of βγ values (0.1-10^{6}), thus excluding nonrelativistic LIPs with βγ as small as 0.1 for the first time.

Light Dark Matter Search with a High-Resolution Athermal Phonon Detector Operated above Ground

We present limits on spin-independent dark matter-nucleon interactions using a 10.6 g Si athermal phonon detector with a baseline energy resolution of σ_{E}=3.86±0.04(stat)_{-0.00}^{+0.19}(syst)  eV. This exclusion analysis sets the most stringent dark matter-nucleon scattering cross-section limits achieved by a cryogenic detector for dark matter particle masses from 93 to 140  MeV/c^{2}, with a raw exposure of 9.9 g d acquired at an above-ground facility. This work illustrates the scientific potential of detectors with athermal phonon sensors with eV-scale energy resolution for future dark matter searches.

Independent component analysis recovers consistent regulatory signals from disparate datasets

The availability of bacterial transcriptomes has dramatically increased in recent years. This data deluge could result in detailed inference of underlying regulatory networks, but the diversity of experimental platforms and protocols introduces critical biases that could hinder scalable analysis of existing data. Here, we show that the underlying structure of the E. coli transcriptome, as determined by Independent Component Analysis (ICA), is conserved across multiple independent datasets, including both RNA-seq and microarray datasets. We subsequently combined five transcriptomics datasets into a large compendium containing over 800 expression profiles and discovered that its underlying ICA-based structure was still comparable to that of the individual datasets. With this understanding, we expanded our analysis to over 3,000 E. coli expression profiles and predicted three high-impact regulons that respond to oxidative stress, anaerobiosis, and antibiotic treatment. ICA thus enables deep analysis of disparate data to uncover new insights that were not visible in the individual datasets.

Cells adapt to diverse environments by regulating gene expression. Genome-wide measurements of gene expression levels have exponentially increased in recent years, but successful integration and analysis of these datasets are limited. Recently, we showed that independent component analysis (ICA), a signal deconvolution algorithm, can separate a large bacterial gene expression dataset into groups of co-regulated genes. This previous study focused on data generated by a standardized pipeline and did not address whether ICA extracts the same quantitative co-expression signals across expression profiling platforms. In this study, we show that ICA finds similar co-regulation patterns underlying multiple gene expression datasets and can be used as a tool to integrate and interpret diverse datasets. Using a dataset containing over 3,000 expression profiles, we predicted three new regulons and characterized their activities. Since large, standardized expression datasets only exist for a few bacterial strains, these results broaden the possible applications of this tool to better understand transcriptional regulation across a wide range of microbes.

Identifying the effect of vancomycin on health care-associated methicillin-resistant Staphylococcus aureus strains using bacteriological and physiological media

BACKGROUND

The evolving antibiotic-resistant behavior of health care-associated methicillin-resistant Staphylococcus aureus (HA-MRSA) USA100 strains are of major concern. They are resistant to a broad class of antibiotics such as macrolides, aminoglycosides, fluoroquinolones, and many more.

FINDINGS

The selection of appropriate antibiotic susceptibility examination media is very important. Thus, we use bacteriological (cation-adjusted Mueller-Hinton broth) as well as physiological (R10LB) media to determine the effect of vancomycin on USA100 strains. The study includes the profiling behavior of HA-MRSA USA100 D592 and D712 strains in the presence of vancomycin through various high-throughput assays. The US100 D592 and D712 strains were characterized at sub-inhibitory concentrations through growth curves, RNA sequencing, bacterial cytological profiling, and exo-metabolomics high throughput experiments.

CONCLUSIONS

The study reveals the vancomycin resistance behavior of HA-MRSA USA100 strains in dual media conditions using wide-ranging experiments.

iModulonDB: a knowledgebase of microbial transcriptional regulation derived from machine learning

Independent component analysis (ICA) of bacterial transcriptomes has emerged as a powerful tool for obtaining co-regulated, independently-modulated gene sets (iModulons), inferring their activities across a range of conditions, and enabling their association to known genetic regulators. By grouping and analyzing genes based on observations from big data alone, iModulons can provide a novel perspective into how the composition of the transcriptome adapts to environmental conditions. Here, we present iModulonDB (imodulondb.org), a knowledgebase of prokaryotic transcriptional regulation computed from high-quality transcriptomic datasets using ICA. Users select an organism from the home page and then search or browse the curated iModulons that make up its transcriptome. Each iModulon and gene has its own interactive dashboard, featuring plots and tables with clickable, hoverable, and downloadable features. This site enhances research by presenting scientists of all backgrounds with co-expressed gene sets and their activity levels, which lead to improved understanding of regulator-gene relationships, discovery of transcription factors, and the elucidation of unexpected relationships between conditions and genetic regulatory activity. The current release of iModulonDB covers three organisms (Escherichia coli, Staphylococcus aureus and Bacillus subtilis) with 204 iModulons, and can be expanded to cover many additional organisms.

Adaptive evolution reveals a tradeoff between growth rate and oxidative stress during naphthoquinone-based aerobic respiration

Evolution fine-tunes biological pathways to achieve a robust cellular physiology. Two and a half billion years ago, rapidly rising levels of oxygen as a byproduct of blooming cyanobacterial photosynthesis resulted in a redox upshift in microbial energetics. The appearance of higher-redox-potential respiratory quinone, ubiquinone (UQ), is believed to be an adaptive response to this environmental transition. However, the majority of bacterial species are still dependent on the ancient respiratory quinone, naphthoquinone (NQ). Gammaproteobacteria can biosynthesize both of these respiratory quinones, where UQ has been associated with aerobic lifestyle and NQ with anaerobic lifestyle. We engineered an obligate NQ-dependent γ-proteobacterium, Escherichia coli ΔubiC, and performed adaptive laboratory evolution to understand the selection against the use of NQ in an oxic environment and also the adaptation required to support the NQ-driven aerobic electron transport chain. A comparative systems-level analysis of pre- and postevolved NQ-dependent strains revealed a clear shift from fermentative to oxidative metabolism enabled by higher periplasmic superoxide defense. This metabolic shift was driven by the concerted activity of 3 transcriptional regulators (PdhR, RpoS, and Fur). Analysis of these findings using a genome-scale model suggested that resource allocation to reactive oxygen species (ROS) mitigation results in lower growth rates. These results provide a direct elucidation of a resource allocation tradeoff between growth rate and ROS mitigation costs associated with NQ usage under oxygen-replete condition.

Functional and Proteomic Analysis of Streptococcus pyogenes Virulence Upon Loss of Its Native Cas9 Nuclease

The public health impact of Streptococcus pyogenes (group A Streptococcus, GAS) as a top 10 cause of infection-related mortality in humans contrasts with its benefit to biotechnology as the main natural source of Cas9 nuclease, the key component of the revolutionary CRISPR-Cas9 gene editing platform. Despite widespread knowledge acquired in the last decade on the molecular mechanisms by which GAS Cas9 achieves precise DNA targeting, the functions of Cas9 in the biology and pathogenesis of its native organism remain unknown. In this study, we generated an isogenic serotype M1 GAS mutant deficient in Cas9 protein and compared its behavior and phenotypes to the wild-type parent strain. Absence of Cas9 was linked to reduced GAS epithelial cell adherence, reduced growth in human whole blood ex vivo, and attenuation of virulence in a murine necrotizing skin infection model. Virulence defects of the GAS Δcas9 strain were explored through quantitative proteomic analysis, revealing a significant reduction in the abundance of key GAS virulence determinants. Similarly, deletion of cas9 affected the expression of several known virulence regulatory proteins, indicating that Cas9 impacts the global architecture of GAS gene regulation.

Primary Laryngotracheal Amyloidosis Masquerading as Malignancy

Amyloidosis represents a heterogeneous group of disorders characterized by the deposition of amyloid protein in various target organs of the body. Amyloidosis is classified as systemic or local. Larynx is the common site for localized amyloid deposition and patient usually presents with hoarseness of voice. Because of the similar clinical and imaging features to malignant laryngeal mass, diagnostic confusion occurs and histopathological confirmation is usually needed. Although laryngeal tracheo-bronchial amyloidosis is rare, it should be considered among the differentials of benign laryngeal tumors.

Characterization of CA-MRSA TCH1516 exposed to nafcillin in bacteriological and physiological media

Cation adjusted-Mueller Hinton Broth (CA-MHB) is the standard bacteriological medium utilized in the clinic for the determination of antibiotic susceptibility. However, a growing number of literature has demonstrated that media conditions can cause a substantial difference in the efficacy of antibiotics and antimicrobials. Recent studies have also shown that minimum inhibitory concentration (MIC) tests performed in standard cell culture media (e.g. RPMI and DMEM) are more indicative of in vivo antibiotic efficacy, presumably because they are a better proxy for the human host’s physiological conditions. The basis for the bacterial media dependent susceptibility to antibiotics remains undefined. To address this question, we characterized the physiological response of methicillin-resistant Staphylococcus aureus (MRSA) during exposure to sub-inhibitory concentrations of the beta-lactam antibiotic nafcillin in either CA-MHB or RPMI + 10% LB (R10LB). Here, we present high quality transcriptomic, exo-metabolomic and morphological data paired with growth and susceptibility results for MRSA cultured in either standard bacteriologic or more physiologic relevant medium.

Design Type(s)	replicate design • transcription profiling design • sequence analysis objective
Measurement Type(s)	transcription profiling assay • cellular morphology • exo-metabolome • growth
Technology Type(s)	RNA sequencing • fluorescence microscopy • liquid chromatography-tandem mass spectrometry • high performance liquid chromatography • Optical Density Measurement
Factor Type(s)	culture medium • biological replicate • experimental condition
Sample Characteristic(s)	Staphylococcus aureus • culturing environment

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Erratum: First Dark Matter Constraints from a SuperCDMS Single-Charge Sensitive Detector [Phys. Rev. Lett. 121, 051301 (2018)]

This corrects the article DOI: 10.1103/PhysRevLett.121.051301.

A computational knowledge-base elucidates the response of Staphylococcus aureus to different media types

S. aureus is classified as a serious threat pathogen and is a priority that guides the discovery and development of new antibiotics. Despite growing knowledge of S. aureus metabolic capabilities, our understanding of its systems-level responses to different media types remains incomplete. Here, we develop a manually reconstructed genome-scale model (GEM-PRO) of metabolism with 3D protein structures for S. aureus USA300 str. JE2 containing 854 genes, 1,440 reactions, 1,327 metabolites and 673 3-dimensional protein structures. Computations were in 85% agreement with gene essentiality data from random barcode transposon site sequencing (RB-TnSeq) and 68% agreement with experimental physiological data. Comparisons of computational predictions with experimental observations highlight: 1) cases of non-essential biomass precursors; 2) metabolic genes subject to transcriptional regulation involved in Staphyloxanthin biosynthesis; 3) the essentiality of purine and amino acid biosynthesis in synthetic physiological media; and 4) a switch to aerobic fermentation upon exposure to extracellular glucose elucidated as a result of integrating time-course of quantitative exo-metabolomics data. An up-to-date GEM-PRO thus serves as a knowledge-based platform to elucidate S. aureus’ metabolic response to its environment.

Environmental perturbations (e.g., antibiotic stress, nutrient starvation, oxidative stress) induce systems-level perturbations of bacterial cells that vary depending on the growth environment. The generation of omics data is aimed at capturing a complete view of the organism’s response under different conditions. Genome-scale models (GEMs) of metabolism represent a knowledge-based platform for the contextualization and integration of multi-omic measurements and can serve to offer valuable insights of system-level responses. This work provides the most up to date reconstruction effort integrating recent advances in the knowledge of S. aureus molecular biology with previous annotations resulting in the first quantitatively and qualitatively validated S. aureus GEM. GEM guided predictions obtained from model analysis provided insights into the effects of medium composition on metabolic flux distribution and gene essentiality. The model can also serve as a platform to guide network reconstructions for other Staphylococci as well as direct hypothesis generation following the integration of omics data sets, including transcriptomics, proteomics, metabolomics, and multi-strain genomic data.

First Dark Matter Constraints from a SuperCDMS Single-Charge Sensitive Detector

We present the first limits on inelastic electron-scattering dark matter and dark photon absorption using a prototype SuperCDMS detector having a charge resolution of 0.1 electron-hole pairs (CDMS HVeV, a 0.93 g CDMS high-voltage device). These electron-recoil limits significantly improve experimental constraints on dark matter particles with masses as low as 1  MeV/c^{2}. We demonstrate a sensitivity to dark photons competitive with other leading approaches but using substantially less exposure (0.49 g d). These results demonstrate the scientific potential of phonon-mediated semiconductor detectors that are sensitive to single electronic excitations.

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. tuberculosis growth in physiological conditions have described an environment that is different from common in vitro media. Thus, elucidating the interplay between available nutrient sources and antibiotic efficacy has clear medical relevance. While genome-scale reconstructions of M. tuberculosis have enabled the ability to interrogate media differences for the past 10 years, recent reconstructions have diverged from each other without standardization. A unified reconstruction of M. tuberculosis H37Rv would elucidate the impact of different nutrient conditions on antibiotic efficacy and provide new insights for therapeutic intervention.

RESULTS

We present a new genome-scale model of M. tuberculosis H37Rv, named iEK1011, that unifies and updates previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations between in vitro and approximated in vivo media conditions to examine the predictive capabilities of iEK1011. The simulated differences recapitulated literature defined characteristics in the rewiring of TCA metabolism including succinate secretion, gluconeogenesis, and activation of both the glyoxylate shunt and the methylcitrate cycle. To assist efforts to elucidate mechanisms of antibiotic resistance development, we curated 16 metabolic genes related to antimicrobial resistance and approximated evolutionary drivers of resistance. Comparing simulations of these antibiotic resistance features between in vivo and in vitro media highlighted condition-dependent differences that may influence the efficacy of antibiotics.

CONCLUSIONS

iEK1011 provides a computational knowledge base for exploring the impact of different environmental conditions on the metabolic state of M. tuberculosis H37Rv. As more experimental data and knowledge of M. tuberculosis H37Rv become available, a unified and standardized M. tuberculosis model will prove to be a valuable resource to the research community studying the systems biology of M. tuberculosis.

Results from the Super Cryogenic Dark Matter Search Experiment at Soudan

We report the result of a blinded search for weakly interacting massive particles (WIMPs) using the majority of the SuperCDMS Soudan data set. With an exposure of 1690 kg d, a single candidate event is observed, consistent with expected backgrounds. This analysis (combined with previous Ge results) sets an upper limit on the spin-independent WIMP-nucleon cross section of 1.4×10^{-44} (1.0×10^{-44})  cm^{2} at 46  GeV/c^{2}. These results set the strongest limits for WIMP-germanium-nucleus interactions for masses >12  GeV/c^{2}.

Patterns of scrotal pain in a hospital setting

Introduction: Scrotal pain is a common urological condition. Common causes of scrotal pain are testicular torsion, epididymitis, epididymo-orchitis and occasionally due to post vasectomy pain, varicocele, testicular trauma etc. The objective of our study is to review the different disease patterns in patients presenting with scrotal pain in a tertiary care hospital.Methods: Patients presenting with scrotal pain to the out-patient clinic and the emergency department were included in the study. All patients were subjected to urinalysis and ultrasound of scrotum with color Doppler study when needed. Descriptive variables were studied and analyzed.Results: Eighty three patients were enrolled in the study during the period of one year. Age ranged from 13 to 72 years; most of the patients were less than 40 years and more than 20 years. Among this age group non-specific orchalgia was very common. Isolated epididymitis was seen in only 4 (4.81%) patients. Epididymo-orchitis was found in 16 (19.27%) patients. Torsion of testis was found in 6 patients (7.22%). The major bulk of the patients presenting with scrotal pain were nonspecific which was found in 39 (46.98%) and exact cause could not be found in them. Total of 15 (18%) patients had acute presentation.Conclusion: Management of Scrotal pain can be simple or at times organ threatening, proper diagnosis and treatment by clinical judgment and necessary investigation is very important.Journal of Society of Surgeons of NepalVol. 17, No. 2, 2014, Page: 31-34

Microbialite response to an anthropogenic salinity gradient in Great Salt Lake, Utah

A railroad causeway across Great Salt Lake, Utah (GSL), has restricted water flow since its construction in 1959, resulting in a more saline North Arm (NA; 24%-31% salinity) and a less saline South Arm (SA; 11%-14% salinity). Here, we characterized microbial carbonates collected from the SA and the NA to evaluate the effect of increased salinity on community composition and abundance and to determine whether the communities present in the NA are still actively precipitating carbonate or if they are remnant features from prior to causeway construction. SSU rRNA gene abundances associated with the NA microbialite were three orders of magnitude lower than those associated with the SA microbialite, indicating that the latter community is more productive. SSU rRNA gene sequencing and functional gene microarray analyses indicated that SA and NA microbialite communities are distinct. In particular, abundant sequences affiliated with photoautotrophic taxa including cyanobacteria and diatoms that may drive carbonate precipitation and thus still actively form microbialites were identified in the SA microbialite; sequences affiliated with photoautotrophic taxa were in low abundance in the NA microbialite. SA and NA microbialites comprise smooth prismatic aragonite crystals. However, the SA microbialite also contained micritic aragonite, which can be formed as a result of biological activity. Collectively, these observations suggest that NA microbialites are likely to be remnant features from prior to causeway construction and indicate a strong decrease in the ability of NA microbialite communities to actively precipitate carbonate minerals. Moreover, the results suggest a role for cyanobacteria and diatoms in carbonate precipitation and microbialite formation in the SA of GSL.

Still-birth--a tragic journey: a critical analysis

Despite improvement in antenatal and intrapartum care, late intrauterine fetal death at and after 28 weeks of gestation remains a persistent and challenging problem to the obstetricians. We undertook the retrospective review of the medical records of 89 women with singleton pregnancy who gave birth to still-born infants at or more than 28 weeks gestation during the period from April 1998 to April 2007 at Nepal Medical College Teaching Hospital to know the prevalence rate and devise preventive measures for still-born infants which accounts more than 50.0% of perinatal death in Nepal. Major malformations were present in 5 (5.6%) of 89 infants including three infants with neural tube abnormalities. Pre-eclampsia preceded the stillbirth and might have been an indirect cause of stillbirth in 16 (19.0%) of 84 women whose infants had normal formations. The cause of still birth in 68 non-pre-eclamptic women was unclear in 31 (45.6%) home breech delivery with head stuck in 11 (16.0%), abruptio placentae in 5 (7.3%), intrauterine fetal growth restriction in 10 (14.7%), infection in 6 (8.8%) and cord accidents in 5 (7.3%). The causes of still births were many and varied, with large population having no obvious cause, although autopsy was not done in any case in this study. Proper monitoring of women with preeclampsia and early diagnosis and prompt delivery for women with abruption placenta might be helpful in reducing the number of stillbirths. Great advocacy with community education on importance of community focused antenatal care and increasing institutional delivery with availability of emergency obstetric care is necessary to decrease the number of stillbirths and perinatal mortality in developing countries like Nepal.

Tamoxifen for Breast Cancer

Breast cancer is one of the common cancers. Hormonal therapy along with surgery, chemotherapy, radiotherapy and targeted therapy are vital modalities for the management of breast cancer. Tamoxifen has been the most widely used hormonal therapy for more than two decades. In this article we review the benefits, dose, duration and timing of Tamoxifen therapy in patients with breast cancer. Keywords: breast cancer, hormonal therapy, tamoxifen.

Tamoxifen for breast cancer

Breast cancer is one of the common cancers. Hormonal therapy along with surgery, chemotherapy, radiotherapy and targeted therapy are vital modalities for the management of breast cancer. Tamoxifen has been the most widely used hormonal therapy for more than two decades. In this article we review the benefits, dose, duration and timing of Tamoxifen therapy in patients with breast cancer.

Live birth following treatment of post molar choriocarcinoma

A G3P(1+1) who underwent dilatation and curettage (D and C) for persistent vaginal bleeding after a month of molar evacuation, underwent successful treatment of choriocarcinoma with methotrexate and was able to have normal baby weighing 2800 gms with good Apgar score and normal placenta. This shows that a normal menstruation and uncomplicated term delivery can be expected after complete chemotherapy for gestational trophoblastic neoplasia (GTN).