Adaptations of Escherichia coli strains to oxidative stress are reflected in properties of their structural proteomes.

BACKGROUND:The reconstruction of metabolic networks and the three-dimensional coverage of protein structures have reached the genome-scale in the widely studied Escherichia coli K-12 MG1655 strain. The combination of the two leads to the formation of a structural systems biology framework, which we have used to analyze differences between the reactive oxygen species (ROS) sensitivity of the proteomes of sequenced strains of E. coli. As proteins are one of the main targets of oxidative damage, understanding how the genetic changes of different strains of a species relates to its oxidative environment can reveal hypotheses as to why these variations arise and suggest directions of future experimental work. RESULTS:Creating a reference structural proteome for E. coli allows us to comprehensively map genetic changes in 1764 different strains to their locations on 4118 3D protein structures. We use metabolic modeling to predict basal ROS production levels (ROStype) for 695 of these strains, finding that strains with both higher and lower basal levels tend to enrich their proteomes with antioxidative properties, and speculate as to why that is. We computationally assess a strain's sensitivity to an oxidative environment, based on known chemical mechanisms of oxidative damage to protein groups, defined by their localization and functionality. Two general groups - metalloproteins and periplasmic proteins - show enrichment of their antioxidative properties between the 695 strains with a predicted ROStype as well as 116 strains with an assigned pathotype. Specifically, proteins that a) utilize a molybdenum ion as a cofactor and b) are involved in the biogenesis of fimbriae show intriguing protective properties to resist oxidative damage. Overall, these findings indicate that a strain's sensitivity to oxidative damage can be elucidated from the structural proteome, though future experimental work is needed to validate our model assumptions and findings. CONCLUSION:We thus demonstrate that structural systems biology enables a proteome-wide, computational assessment of changes to atomic-level physicochemical properties and of oxidative damage mechanisms for multiple strains in a species. This integrative approach opens new avenues to study adaptation to a particular environment based on physiological properties predicted from sequence alone

Relationship between social support, quality of life, and Th2 cytokines in a biobehavioral cancer survivorship trial.

ObjectiveBenefits of social support (SS) during cancer survivorship are complex. This study examines change in SS over time in cervical cancer (CXCA) survivors who have completed definitive treatment and how changing SS impacts quality of life (QOL) and T-helper type 2 (Th2) cytokines.MethodsWe conducted a randomized trial in 204 CXCA survivors to test if psychosocial telephone counseling (PTC) could improve QOL compared to usual care (UC). Although PTC did not target SS, data were collected at baseline, 4 and 9 months post-enrollment using the Medical Outcomes Survey Social Support scale. Biospecimens were collected to investigate associations with patient-reported outcomes. Data were analyzed using multivariate linear models and stepwise regression.ResultsParticipants' mean age was 43. PTC participants experienced increasing SS compared to UC at 4 months (PTC-UC = 5.1; p = 0.055) and 9 months (PTC-UC = 6.0; p = 0.046). Higher baseline SS and increasing SS were independently associated with improved QOL at 4 and 9 months after adjusting for patient characteristics (p < 0.05). Differences between study arms were not statistically significant. Improvements in QOL at 4 months were observed with increases in emotional/informational and tangible SS. Increasing SS predicted significant longitudinal decreases in IL-4 and IL-13 at 4 months that were larger in the PTC arm (interactions p = 0.041 and p = 0.057, respectively).ConclusionImproved SS was significantly associated with improved QOL independent of patient characteristics and study arm. Decreasing Th2 cytokines with increasing SS and QOL are consistent with a biobehavioral paradigm in which modulation of the chronic stress response is associated with shifts in immune stance

Validation of PROMIS emotional distress short form scales for cervical cancer.

ObjectivesCervical cancer patients are at high risk for emotional distress. In this study we evaluate the PROMIS emotional distress-Depression and -Anxiety Short Forms for assessing depression and anxiety in a cervical cancer population.MethodsA 15-item questionnaire was used in a cervical cancer biobehavioral randomized clinical trial, testing psychosocial telephone counseling (PTC) against usual care (UC). It was administered to 204 patients prior to randomization, four months post-enrollment, and nine months post-enrollment, together with legacy measures of depression. The short forms were evaluated in patients participating in this study over three time points for internal consistency, convergent validity, and responsiveness to change over time.ResultsOverall, 45% and 47% of patients scored in the moderate to severe range for anxiety and depression, respectively. Internal consistency coefficients were ≥ 0.95 at baseline, 4 months, and 9 months for depression and anxiety. The average inter-item correlation was 0.65 and 0.73 at baseline assessment for depression and anxiety, respectively. The depression short form T-score was correlated with legacy distress scales ranging from 0.44-0.76, and the anxiety short form ranging from 0.45-0.78. The depression short form demonstrated sensitivity to change as patients randomized to the counseling intervention reported greater improvement over time in depression (p = 0.014), and a nonsignificant improvement in anxiety, compared to the patients receiving usual care.ConclusionsThe PROMIS depression and anxiety short forms reliably and validly assess cervical cancer-specific emotional distress, capture salient features of distress in this population, and perform as well or better than legacy measures

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance.

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many publicly available datasets describing its AMR characteristics demand disparate data-type analyses. Here, we develop a reference strain-agnostic computational platform that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics. This platform is applied to 1595 sequenced strains to yield four key results. First, a pan-genome analysis shows that M. tuberculosis is highly conserved with sequenced variation concentrated in PE/PPE/PGRS genes. Second, the platform corroborates 33 genes known to confer resistance and identifies 24 new genetic signatures of AMR. Third, 97 epistatic interactions across 10 resistance classes are revealed. Fourth, detailed structural analysis of these genes yields mechanistic bases for their selection. The platform can be used to study other human pathogens

Interferon gamma replacement as salvage therapy in chronic pulmonary aspergillosis: effects on frequency of acute exacerbation and all-cause hospital admission.

Chronic pulmonary aspergillosis (CPA) is often poorly responsive to antifungal treatment; secondary infections increase morbidity/mortality, particularly in progressive cases. Interferon gamma (IFNγ) has been implicated in not only Aspergillus control but also bacterial clearance. Clinical notes of patients with CPA treated with IFNγ (2011-2018) were retrospectively hand-searched. In patients treated for >12 months (n=20), the frequency of acute exacerbation reduced from 3.1 to 1.4 episodes/year (p=0.006) in the 12 months after treatment initiation compared with the 12 months before. A significant reduction in the frequency of hospital admissions/year was also observed (0.8 to 0.3, p=0.04). These findings support further prospective studies

Using Genome-scale Models to Predict Biological Capabilities

Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellular growth capabilities on various substrates and the effect of gene knockouts at the genome scale. Thus, much interest has developed in understanding and applying these methods to areas such as metabolic engineering, antibiotic design, and organismal and enzyme evolution. This Primer will get you started

Burden of SARS-CoV-2 infection in healthcare workers during second wave in England and impact of vaccines : prospective multicentre cohort study (SIREN) and mathematical model

Funding: The study is funded by the Department of Health and Social Care (DHSC) and UK Health Security Agency (UKHSA; formally Public Health England), with contributions from the governments of Northern Ireland, Scotland, and Wales. Funding was also provided by the National Institute for Health Research (NIHR) as an Urgent Public Health Priority Study and through the Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance (NIHR200915), a partnership between UKHSA and the University of Oxford.OBJECTIVE: To describe the incidence of, risk factors for, and impact of vaccines on primary SARS-CoV-2 infection during the second wave of the covid-19 pandemic in susceptible hospital healthcare workers in England. DESIGN: Multicentre prospective cohort study. SETTING: National Health Service secondary care health organisations (trusts) in England between 1 September 2020 and 30 April 2021. PARTICIPANTS: Clinical, support, and administrative staff enrolled in the SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) study with no evidence of previous infection. Vaccination status was obtained from national covid-19 vaccination registries and self-reported. MAIN OUTCOME MEASURE: SARS-CoV-2 infection confirmed by polymerase chain reaction. Mixed effects logistic regression was conducted to determine demographic and occupational risk factors for infection, and an individual based mathematical model was used to predict how large the burden could have been if vaccines had not been available from 8 December 2020 . RESULTS: During England's second wave, 12.9% (2353/18 284) of susceptible SIREN participants became infected with SARS-CoV-2. Infections peaked in late December 2020 and decreased from January 2021, concurrent with the cohort's rapid vaccination coverage and a national lockdown. In multivariable analysis, factors increasing the likelihood of infection in the second wave were being under 25 years old (20.3% (132/651); adjusted odds ratio 1.35, 95% confidence interval 1.07 to 1.69), living in a large household (15.8% (282/1781); 1.54, 1.23 to 1.94, for participants from households of five or more people), having frequent exposure to patients with covid-19 (19.2% (723/3762); 1.79, 1.56 to 2.06, for participants with exposure every shift), working in an emergency department or inpatient ward setting (20.8% (386/1855); 1.76, 1.45 to 2.14), and being a healthcare assistant (18.1% (267/1479); 1.43, 1.16 to 1.77). Time to first vaccination emerged as being strongly associated with infection (P<0.001), with each additional day multiplying a participant's adjusted odds ratio by 1.02. Mathematical model simulations indicated that an additional 9.9% of all patient facing hospital healthcare workers would have been infected were it not for the rapid vaccination coverage. CONCLUSIONS: The rapid covid-19 vaccine rollout from December 2020 averted infection in a large proportion of hospital healthcare workers in England: without vaccines, second wave infections could have been 69% higher. With booster vaccinations being needed for adequate protection from the omicron variant, and perhaps the need for further boosters for future variants, ensuring equitable delivery to healthcare workers is essential. The findings also highlight occupational risk factors that persisted in healthcare workers despite vaccine rollout; a greater understanding of the transmission dynamics responsible for these is needed to help to optimise the infection prevention and control policies that protect healthcare workers from infection and therefore to support staffing levels and maintain healthcare provision. TRIAL REGISTRATION: ISRCTN registry ISRCTN11041050.Publisher PDFPeer reviewe

Differential expression of PPP1R12A transcripts, including those harbouring alternatively spliced micro-exons, in placentae from complicated pregnancies

Introduction Placenta-associated pregnancy complications, including pre-eclampsia (PE) and intrauterine growth restriction (IUGR) are conditions postulated to originate from initial failure of placentation, leading to clinical sequelae indicative of endothelial dysfunction. Vascular smooth muscle aberrations have also been implicated in the pathogenesis of both disorders via smooth muscle contractility and relaxation mediated by Myosin Light Chain Phosphatase (MLCP) and the oppositional contractile action of Myosin Light Chain Kinase. PPP1R12A is a constituent part of the MLCP complex responsible for dephosphorylation of myosin fibrils. We hypothesize that alternative splicing of micro-exons result in isoforms lacking the functional leucine zipper (LZ) domain which may give those cells expressing these alternative transcripts a tendency towards contraction and vasoconstriction. Methods Expression was determined by qRT-PCR. Epigenetic profiling consisted of bisulphite-based DNA methylation analysis and ChIP for underlying histone modifications. Results We identified several novel transcripts with alternative micro-exon inclusion that would produce LZ- PPP1R12A protein. qRT-PCR revealed some isoforms, including the PPP1R12A canonical transcript, are differentially expressed in placenta biopsies from PE and IUGR samples compared to uncomplicated pregnancies. Discussion We propose that upregulation of PPP1R12A expression in complicated pregnancies may be due to enhanced promoter activity leading to increased transcription as a response to physiological stress in the placenta, which we show is independent of promoter DNA methylation