Activity-Based Protein Profiling for the Identification of Novel Carbohydrate-Active Enzymes Involved in Xylan Degradation in the Hyperthermophilic Euryarchaeon Thermococcus sp. Strain 2319x1E

Activity-based protein profiling (ABPP) has so far scarcely been applied in Archaea in general and, especially, in extremophilic organisms. We herein isolated a novel Thermococcus strain designated sp. strain 2319x1E derived from the same enrichment culture as the recently reported Thermococcus sp. strain 2319x1. Both strains are able to grow with xylan as the sole carbon and energy source, and for Thermococcus sp. strain 2319x1E (optimal growth at 85°C, pH 6–7), the induction of xylanolytic activity in the presence of xylan was demonstrated. Since the solely sequence-based identification of xylanolytic enzymes is hardly possible, we established a complementary approach by conducting comparative full proteome analysis in combination with ABPP using α- or β-glycosidase selective probes and subsequent mass spectrometry (MS)-based analysis. This complementary proteomics approach in combination with recombinant protein expression and classical enzyme characterization enabled the identification of a novel bifunctional maltose-forming α-amylase and deacetylase (EGDIFPOO_00674) belonging to the GH57 family and a promiscuous β-glycosidase (EGIDFPOO_00532) with β-xylosidase activity. We thereby further substantiated the general applicability of ABPP in archaea and expanded the ABPP repertoire for the identification of glycoside hydrolases in hyperthermophiles.

Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling

The development of cancer therapies may be improved by the discovery of tumor-specific molecular dependencies. The requisite tools include genetic and chemical perturbations, each with its strengths and limitations. Drug perturbations can be readily applied to primary cancer samples at a large scale, but mechanistic understanding of hits and further pharmaceutical development is often complicated by the fact that a small compound has a range of affinities to multiple proteins. To computationally infer the molecular dependencies of individual cancers from their ex-vivo drug sensitivity profiles, we developed a mathematical model that deconvolutes these data using measurements of protein-drug affinity profiles. Our method, DepInfeR, correctly identified known dependencies, including EGFR dependence in Her2+ breast cancer cell line, FLT3 dependence in AML tumors with FLT3-ITD mutations, and the differential dependencies on the B-cell receptor pathway in two major subtypes of chronic lymphocytic leukemia (CLL). Furthermore, our method uncovered new subgroup-specific dependencies, including a previously unreported dependence of high-risk CLL on Checkpoint kinase 1 (CHEK1). The method also produced a more accurate map of the molecular dependencies in a heterogeneous set of 117 CLL samples. The ability to deconvolute polypharmacological phenotypes into underlying causal molecular dependencies should increase the utility of high-throughput drug response assays for functional precision oncology.

Proteomic Profile Mapping and Differential Expression of Protein in Ovarian Cancer

This study aimed to characterize differentially expressed proteins in malignant ovarian tissue to find out potential novel biomarkers in ovarian cancer (OC). We enrolled 20 ovarian cancer patients (40-65 years) and an equal number of age-matched healthy women to get malignant and healthy ovarian tissue samples for protein extraction and quantification after tissue lysis. The protein profile was analyzed using two-dimensional gel electrophoresis followed by MALDI-TOF mass spectrometry. Based on the information thus obtained, the proteins were identified using the relevant software and protein databank to analyze the malignant and non-malignant ovarian tissue samples (n = 20/group). In this proteomic analysis of the ovarian tissue, 112 proteins were detected. Based on a minimum of ≥ 1.5-fold expression difference (p-value ≤ 0.05; FDR ≤ 0.05 and PMF ≥ 79), 17 proteins were found to be upregulated while 27 were downregulated in the malignant ovarian tissue. Six of these proteins have not been previously reported in ovarian cancer. Out of these, three are upregulated while the other three are downregulated. The upregulated proteins are centrosomal protein of 290 kDa (Cep290), uncharacterized protein C1orf109 (C1orf109) and GTPase-activating Rap/Ran-GAP domain-like protein 3 (GARNL3), and the three downregulated proteins identified are actin-related protein 3 (ARP3), cytosolic carboxypeptidase 3 (AGBL3) and NADH dehydrogenase [ubiquinone] 1 alpha subcomplex subunit 10 (NDUFA10). This proteomic mapping not only provides data on protein profiling of ovarian cancer in Pakistani population for the first time but also reports six novel differentially expressed proteins, which have not been previously reported in ovarian cancer patients. They may serve as potential novel biomarkers after further validation for early diagnosis and prognosis of ovarian cancer. It also provides additional data to improve existing knowledge of already reported protein ovarian cancer biomarkers.

Clinical characteristics with inflammation profiling of Long-COVID and association with one-year recovery following hospitalisation in the UK: a prospective observational study

Background There are currently no effective pharmacological or non-pharmacological interventions for Long-COVID. To identify potential therapeutic targets, we focussed on previously described four recovery clusters five months after hospital discharge, their underlying inflammatory profiles and relationship with clinical outcomes at one year. Methods PHOSP-COVID is a prospective longitudinal cohort study, recruiting adults hospitalised with COVID-19 across the UK. Recovery was assessed using patient reported outcomes measures (PROMs), physical performance, and organ function at five-months and one-year after hospital discharge. Hierarchical logistic regression modelling was performed for patient-perceived recovery at one-year. Cluster analysis was performed using clustering large applications (CLARA) k-medoids approach using clinical outcomes at five-months. Inflammatory protein profiling from plasma at the five-month visit was performed. Findings 2320 participants have been assessed at five months after discharge and 807 participants have completed both five-month and one-year visits. Of these, 35.6% were female, mean age 58.7 (SD 12.5) years, and 27.8% received invasive mechanical ventilation (IMV). The proportion of patients reporting full recovery was unchanged between five months 501/165 (25.6%) and one year 232/804 (28.9%). Factors associated with being less likely to report full recovery at one year were: female sex OR 0.68 (95% CI 0.46-0.99), obesity OR 0.50 (95%CI 0.34-0.74) and IMV OR 0.42 (95%CI 0.23-0.76). Cluster analysis (n=1636) corroborated the previously reported four clusters: very severe, severe, moderate/cognitive, mild relating to the severity of physical, mental health and cognitive impairments at five months in a larger sample. There was elevation of inflammatory mediators of tissue damage and repair in both the very severe and the moderate/cognitive clusters compared to the mild cluster including interleukin-6 which was elevated in both comparisons. Overall, there was a substantial deficit in median (IQR) EQ5D-5L utility index from pre-COVID (retrospective assessment) 0.88 (0.74-1.00), five months 0.74 (0.60-0.88) to one year: 0.74 (0.59-0.88), with minimal improvements across all outcome measures at one-year after discharge in the whole cohort and within each of the four clusters. Interpretation The sequelae of a hospital admission with COVID-19 remain substantial one year after discharge across a range of health domains with the minority in our cohort feeling fully recovered. Patient perceived health-related quality of life remains reduced at one year compared to pre-hospital admission. Systematic inflammation and obesity are potential treatable traits that warrant further investigation in clinical trials.

Posiphen Reduces the Levels of Huntingtin Protein through Translation Suppression

Posiphen tartrate (Posiphen) is an orally available small molecule that targets a conserved regulatory element in the mRNAs of amyloid precursor protein (APP) and α-synuclein (αSYN) and inhibits their translation. APP and αSYN can cause neurodegeneration when their aggregates induce neurotoxicity. Therefore, Posiphen is a promising drug candidate for neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease. Posiphen’s safety has been demonstrated in three independent phase I clinical trials. Moreover, in a proof of concept study, Posiphen lowered neurotoxic proteins and inflammatory markers in cerebrospinal fluid of mild cognitive impaired patients. Herein we investigated whether Posiphen reduced the expression of other proteins, as assessed by stable isotope labeling with amino acids in cell culture (SILAC) followed by mass spectrometry (MS)-based proteomics. Neuroblastoma SH-SY5Y cells, an in vitro model of neuronal function, were used for the SILAC protein profiling response. Proteins whose expression was altered by Posiphen treatment were characterized for biological functions, pathways and networks analysis. The most significantly affected pathway was the Huntington’s disease signaling pathway, which, along with huntingtin (HTT) protein, was down-regulated by Posiphen in the SH-SY5Y cells. The downregulation of HTT protein by Posiphen was confirmed by quantitative Western blotting and immunofluorescence. Unchanged mRNA levels of HTT and a comparable decay rate of HTT proteins after Posiphen treatment supported the coclusion that Posiphen reduced HTT via downregulation of the translation of HTT mRNA. Meanwhile, the downregulation of APP and αSYN proteins by Posiphen was also confirmed. The mRNAs encoding HTT, APP and αSYN contain an atypical iron response element (IRE) in their 5′-untranslated regions (5′-UTRs) that bind iron regulatory protein 1 (IRP1), and Posiphen specifically bound this complex. Conversely, Posiphen did not bind the IRP1/IRE complex of mRNAs with canonical IREs, and the translation of these mRNAs was not affected by Posiphen. Taken together, Posiphen shows high affinity binding to the IRE/IRP1 complex of mRNAs with an atypical IRE stem loop, inducing their translation suppression, including the mRNAs of neurotoxic proteins APP, αSYN and HTT.