A simple principle concerning the robustness of protein complex activity to changes in gene expression

<p>Abstract</p> <p>Background</p> <p>The functions of a eukaryotic cell are largely performed by multi-subunit protein complexes that act as molecular machines or information processing modules in cellular networks. An important problem in systems biology is to understand how, in general, these molecular machines respond to perturbations.</p> <p>Results</p> <p>In yeast, genes that inhibit growth when their expression is reduced are strongly enriched amongst the subunits of multi-subunit protein complexes. This applies to both the core and peripheral subunits of protein complexes, and the subunits of each complex normally have the same loss-of-function phenotypes. In contrast, genes that inhibit growth when their expression is increased are not enriched amongst the core or peripheral subunits of protein complexes, and the behaviour of one subunit of a complex is not predictive for the other subunits with respect to over-expression phenotypes.</p> <p>Conclusion</p> <p>We propose the principle that the overall activity of a protein complex is in general robust to an increase, but not to a decrease in the expression of its subunits. This means that whereas phenotypes resulting from a decrease in gene expression can be predicted because they cluster on networks of protein complexes, over-expression phenotypes cannot be predicted in this way. We discuss the implications of these findings for understanding how cells are regulated, how they evolve, and how genetic perturbations connect to disease in humans.</p

Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection:protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales

IntroductionSARS-CoV-2 infection rarely causes hospitalisation in children and young people (CYP), but mild or asymptomatic infections are common. Persistent symptoms following infection have been reported in CYP but subsequent healthcare use is unclear. We aim to describe healthcare use in CYP following community-acquired SARS-CoV-2 infection and identify those at risk of ongoing healthcare needs.Methods and analysisWe will use anonymised individual-level, population-scale national data linking demographics, comorbidities, primary and secondary care use and mortality between 1 January 2019 and 1 May 2022. SARS-CoV-2 test data will be linked from 1 January 2020 to 1 May 2022. Analyses will use Trusted Research Environments: OpenSAFELY in England, Secure Anonymised Information Linkage (SAIL) Databank in Wales and Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 in Scotland (EAVE-II). CYP aged ≥4 and &lt;18 years who underwent SARS-CoV-2 reverse transcription PCR (RT-PCR) testing between 1 January 2020 and 1 May 2021 and those untested CYP will be examined.The primary outcome measure is cumulative healthcare cost over 12 months following SARS-CoV-2 testing, stratified into primary or secondary care, and physical or mental healthcare. We will estimate the burden of healthcare use attributable to SARS-CoV-2 infections in the 12 months after testing using a matched cohort study of RT-PCR positive, negative or untested CYP matched on testing date, with adjustment for confounders. We will identify factors associated with higher healthcare needs in the 12 months following SARS-CoV-2 infection using an unmatched cohort of RT-PCR positive CYP. Multivariable logistic regression and machine learning approaches will identify risk factors for high healthcare use and characterise patterns of healthcare use post infection.Ethics and disseminationThis study was approved by the South-Central Oxford C Health Research Authority Ethics Committee (13/SC/0149). Findings will be preprinted and published in peer-reviewed journals. Analysis code and code lists will be available through public GitHub repositories and OpenCodelists with meta-data via HDR-UK Innovation Gateway

Tobacco Smoke Mediated Induction of Sinonasal Microbial Biofilms

Cigarette smokers and those exposed to second hand smoke are more susceptible to life threatening infection than non-smokers. While much is known about the devastating effect tobacco exposure has on the human body, less is known about the effect of tobacco smoke on the commensal and commonly found pathogenic bacteria of the human respiratory tract, or human respiratory tract microbiome. Chronic rhinosinusitis (CRS) is a common medical complaint, affecting 16% of the US population with an estimated aggregated cost of $6 billion annually. Epidemiologic studies demonstrate a correlation between tobacco smoke exposure and rhinosinusitis. Although a common cause of CRS has not been defined, bacterial presence within the nasal and paranasal sinuses is assumed to be contributory. Here we demonstrate that repetitive tobacco smoke exposure induces biofilm formation in a diverse set of bacteria isolated from the sinonasal cavities of patients with CRS. Additionally, bacteria isolated from patients with tobacco smoke exposure demonstrate robust in vitro biofilm formation when challenged with tobacco smoke compared to those isolated from smoke naïve patients. Lastly, bacteria from smoke exposed patients can revert to a non-biofilm phenotype when grown in the absence of tobacco smoke. These observations support the hypothesis that tobacco exposure induces sinonasal biofilm formation, thereby contributing to the conversion of a transient and medically treatable infection to a persistent and therapeutically recalcitrant condition

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain–gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials

An autologous dendritic cell vaccine polarizes a Th-1 response which is tumoricidal to patient-derived breast cancer cells.

Breast cancer remains one of the leading causes of cancer-associated death worldwide. Conventional treatment is associated with substantial toxicity and suboptimal efficacy. We, therefore, developed and evaluated the in vitro efficacy of an autologous dendritic cell (DC) vaccine to treat breast cancer. We recruited 12 female patients with stage 1, 2, or 3 breast cancer and matured their DCs with autologous tumour-specific lysate, a toll-like receptor (TLR)-3 and 7/8 agonist, and an interferon-containing cocktail. The efficacy of the vaccine was evaluated by its ability to elicit a cytotoxic T-lymphocyte response to autologous breast cancer cells in vitro. Matured DCs (≥ 60% upregulation of CD80, CD86, CD83, and CCR7) produced high levels of the Th1 effector cytokine, IL12-p70 (1.2 ng/ml; p < 0.0001), compared to DCs pulsed with tumour lysate, or matured with an interferon-containing cocktail alone. We further showed that matured DCs enhance antigen-specific CD8 + T-cell responses to HER-2 (4.5%; p < 0.005) and MUC-1 (19%; p < 0.05) tetramers. The mature DCs could elicit a robust and dose-dependent antigen-specific cytotoxic T-lymphocyte response (65%) which was tumoricidal to autologous breast cancer cells in vitro compared to T-lymphocytes that were primed with autologous lysate loaded-DCs (p < 0.005). Lastly, we showed that the mature DCs post-cryopreservation maintained high viability, maintained their mature phenotype, and remained free of endotoxins or mycoplasma. We have developed a DC vaccine that is cytotoxic to autologous breast cancer cells in vitro. The tools and technology generated here will now be applied to a phase I/IIa clinical trial