Inhibition of leukotriene-B4 signalling-mediated host response to tuberculosis is a potential mode of adjunctive host-directed therapy

Treatment of tuberculosis (TB) is faced with several challenges including the long treatment duration, drug toxicity and tissue pathology. Host-directed therapy provides promising avenues to find compounds for adjunctively assisting antimycobacterials in the TB treatment regimen, by promoting pathogen eradication or limiting tissue destruction. Eicosanoids are a class of lipid molecules that are potent mediators of inflammation and have been implicated in aspects of the host response against TB. Here, we have explored the blood transcriptome of pulmonary TB patients to understand the activity of leukotriene B4, a pro-inflammatory eicosanoid. Our study shows a significant upregulation in the leukotriene B4 signalling pathway in active TB patients, which is reversed with TB treatment. We have further utilized our in-house network analysis algorithm, ResponseNet, to identify potential downstream signal effectors of leukotriene B4 in TB patients including STAT1/2 and NADPH oxidase at a systemic as well as local level, followed by experimental validation of the same. Finally, we show the potential of inhibiting leukotriene B4 signalling as a mode of adjunctive host-directed therapy against TB. This study provides a new mode of TB treatment along with mechanistic insights which can be further explored in pre-clinical trials.

CRD: A de novo design algorithm for the prediction of cognate protein receptors for small molecule ligands

While predicting a ligand that binds to a protein is feasible with current methods, the opposite, i.e., the prediction of a receptor for a ligand remains challenging. We present an approach for predicting receptors of a given ligand that uses de novo design and structural bioinformatics. We have developed the algorithm CRD, comprising multiple modules combining fragment-based sub-site finding, a machine learning function to estimate the size of the site, a genetic algorithm that encodes knowledge on protein structures and a physics-based fitness scoring scheme. CRD includes a pseudo-receptor design component followed by a mapping component to identify proteins that might contain these sites. CRD recovers the sites and receptors of several natural ligands. It designs similar sites for similar ligands, yet to some extent can distinguish between closely related ligands. CRD correctly predicts receptor classes for several drugs and might become a valuable tool for drug discovery.

Prevalence and Clinical Significance of Electrocardiographic Complete Right Bundle Branch Block in Young Individuals

BACKGROUND AND AIMS

There is limited information on the clinical significance of complete right bundle branch block (CRBBB) in young individuals. The aim of this study was to determine the prevalence and significance of CRBBB in a large cohort of young individuals aged 14-35 years old.

METHODS

From 2008 to 2018, 104,369 consecutive individuals underwent a cardiovascular assessment with a health questionnaire, electrocardiogram, clinical consultation, and selective echocardiography. Follow-up was obtained via direct telephone consultations. Mean follow-up was 7.3 ± 2.7 years.

RESULTS

CRBBB was identified in 154 (0.1%) individuals and was more prevalent in males compared with females (0.20% vs. 0.06%; p<0.05) and in athletes compared with non-athletes (0.25% vs. 0.14%; p<0.05). CRBBB-related cardiac conditions were identified in 7 (5%) individuals (4 with atrial septal defect, 1 with Brugada syndrome, 1 with progressive cardiac conduction disease and 1 with atrial fibrillation). Pathology was more frequently identified in individuals with non-isolated CRBBB compared with individuals with isolated CRBBB (14% vs 1%; p < 0.05) and in individuals with a QRS duration of ≥130 milliseconds (ms) compared with individuals with a QRS of <130ms (10% vs 1%; p<0.05).

CONCLUSION

The prevalence of CRBBB in young individuals was 0.1% and was more prevalent in males and athletes. CRBBB-related conditions were identified in 5% of individuals and were more common in individuals with non-isolated CRBBB and more pronounced intraventricular conduction delay (QRS duration of ≥130ms). Secondary evaluation should be considered for young individuals with CRBBB with symptoms, concerning family history, additional electrocardiographic anomalies or significant QRS prolongation (≥130ms).

A novel stop-loss mutation in NKX2-2 gene as a cause of neonatal diabetes mellitus: molecular characterization and structural analysis

AIM

To identify the genetic etiology of neonatal diabetes in an infant and to elucidate the molecular mechanism of the identified mutation underlying the pathogenesis.

METHODS

Genetic analysis was carried out by sequencing of known etiological genes associated with NDM. Molecular characterization was performed by constructing a identified mutation in NKX2-2 gene and  functional aspects was tested using transactivation, protein expression, DNA binding, nuclear localization assays. Structural analysis was performed by modeling the NKX2-2 protein structure.

RESULTS

A novel homozygous frameshift mutation  c.772delC, p.Q258SFs*59 in the NKX2-2 gene was identified in a patient with neonatal diabetes. Functional studies revealed that this mutation resulted in an elongated protein sequence, affecting DNA binding activity and transcriptional function. Structural analysis suggested alterations in the protein's tertiary structure, likely contributing to its dysfunction.

CONCLUSION

This study presents the first report of a stop-loss mutation in the NKX2-2 gene associated with NDM. Our findings emphasize the importance of functional and structural characterization to understand the biological consequences of such mutations. This comprehensive analysis provides insights into the molecular mechanisms underlying NDM and its clinical phenotype, which may aid in better diagnosis and management of patients with similar variants in the future.

Cysteine desulfurase (IscS)-mediated fine-tuning of bioenergetics and SUF expression prevents Mycobacterium tuberculosis hypervirulence

Iron-sulfur (Fe-S) biogenesis requires multiprotein assembly systems, SUF and ISC, in most prokaryotes. M. tuberculosis (Mtb) encodes a complete SUF system, the depletion of which was bactericidal. The ISC operon is truncated to a single gene iscS (cysteine desulfurase), whose function remains uncertain. Here, we show that MtbΔiscS is bioenergetically deficient and hypersensitive to oxidative stress, antibiotics, and hypoxia. MtbΔiscS resisted killing by nitric oxide (NO). RNA sequencing indicates that IscS is important for expressing regulons of DosR and Fe-S-containing transcription factors, WhiB3 and SufR. Unlike wild-type Mtb, MtbΔiscS could not enter a stable persistent state, continued replicating in mice, and showed hypervirulence. The suf operon was overexpressed in MtbΔiscS during infection in a NO-dependent manner. Suppressing suf expression in MtbΔiscS either by CRISPR interference or upon infection in inducible NO-deficient mice arrests hypervirulence. Together, Mtb redesigned the ISC system to "fine-tune" the expression of SUF machinery for establishing persistence without causing detrimental disease in the host.

Structural similarities between SAM and ATP recognition motifs and detection of ATP binding in a SAM binding DNA methyltransferase

S-adenosylmethionine (SAM) is a ubiquitous co-factor that serves as a donor for methylation reactions and additionally serves as a donor of other functional groups such as amino and ribosyl moieties in a variety of other biochemical reactions. Such versatility in function is enabled by the ability of SAM to be recognized by a wide variety of protein molecules that vary in their sequences and structural folds. To understand what gives rise to specific SAM binding in diverse proteins, we set out to study if there are any structural patterns at their binding sites. A comprehensive analysis of structures of the binding sites of SAM by all-pair comparison and clustering, indicated the presence of 4 different site-types, only one among them being well studied. For each site-type we decipher the common minimum principle involved in SAM recognition by diverse proteins and derive structural motifs that are characteristic of SAM binding. The presence of the structural motifs with precise three-dimensional arrangement of amino acids in SAM sites that appear to have evolved independently, indicates that these are winning arrangements of residues to bring about SAM recognition. Further, we find high similarity between one of the SAM site types and a well known ATP binding site type. We demonstrate using in vitro experiments that a known SAM binding protein, HpyAII.M1, a type 2 methyltransferase can bind and hydrolyse ATP. We find common structural motifs that explain this, further supported through site-directed mutagenesis. Observation of similar motifs for binding two of the most ubiquitous ligands in multiple protein families with diverse sequences and structural folds presents compelling evidence at the molecular level in favour of convergent evolution.

PathTracer Comprehensively Identifies Hypoxia-Induced Dormancy Adaptations in Mycobacterium tuberculosis

Mining large-scale data to discover biologically relevant information remains a challenge despite the rapid development of bioinformatics tools. Here, we have developed a new tool, PathTracer, to identify biologically relevant information flows by mining genome-wide protein-protein interaction networks following integration of gene expression data. PathTracer successfully mines interactions between genes and traces the most perturbed paths of perceived activities under the conditions of the study. We further demonstrated the utility of this tool by identifying adaptation mechanisms of hypoxia-induced dormancy in Mycobacterium tuberculosis (Mtb).

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. Identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

Biosensor-integrated transposon mutagenesis reveals rv0158 as a coordinator of redox homeostasis in Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is evolutionarily equipped to resist exogenous reactive oxygen species (ROS) but shows vulnerability to an increase in endogenous ROS (eROS). Since eROS is an unavoidable consequence of aerobic metabolism, understanding how Mtb manages eROS levels is essential yet needs to be characterized. By combining the Mrx1-roGFP2 redox biosensor with transposon mutagenesis, we identified 368 genes (redoxosome) responsible for maintaining homeostatic levels of eROS in Mtb. Integrating redoxosome with a global network of transcriptional regulators revealed a hypothetical protein (Rv0158) as a critical node managing eROS in Mtb. Disruption of rv0158 (rv0158 KO) impaired growth, redox balance, respiration, and metabolism of Mtb on glucose but not on fatty acids. Importantly, rv0158 KO exhibited enhanced growth on propionate, and the Rv0158 protein directly binds to methylmalonyl-CoA, a key intermediate in propionate catabolism. Metabolite profiling, ChIP-Seq, and gene-expression analyses indicate that Rv0158 manages metabolic neutralization of propionate toxicity by regulating the methylcitrate cycle. Disruption of rv0158 enhanced the sensitivity of Mtb to oxidative stress, nitric oxide, and anti-TB drugs. Lastly, rv0158 KO showed poor survival in macrophages and persistence defect in mice. Our results suggest that Rv0158 is a metabolic integrator for carbon metabolism and redox balance in Mtb.

Systems-level profiling of early peripheral host-response landscape variations across COVID-19 severity states in an Indian cohort

Host immune response to COVID-19 plays a significant role in regulating disease severity. Although big data analysis has provided significant insights into the host biology of COVID-19 across the world, very few such studies have been performed in the Indian population. This study utilizes a transcriptome-integrated network analysis approach to compare the immune responses between asymptomatic or mild and moderate-severe COVID-19 patients in an Indian cohort. An immune suppression phenotype is observed in the early stages of moderate-severe COVID-19 manifestation. A number of pathways are identified that play crucial roles in the host control of the disease such as the type I interferon response and classical complement pathway which show different activity levels across the severity spectrum. This study also identifies two transcription factors, IRF7 and ESR1, to be important in regulating the severity of COVID-19. Overall this study provides a deep understanding of the peripheral immune landscape in the COVID-19 severity spectrum in the Indian genetic background and opens up future research avenues to compare immune responses across global populations.

Salmonella Typhimurium PgtE is an essential arsenal to defend against the host resident antimicrobial peptides

Salmonella enterica serovar Typhimurium is a common cause of gastroenteritis in humans and occasionally causes systemic infection. Salmonella's ability to survive and replicate within macrophages is an important characteristic during systemic infection. The outer membrane protease PgtE of S. enterica is a member of the Omptin family of outer membrane aspartate proteases which has well-characterized proteolytic activities in-vitro against a wide range of physiologically relevant substrates. However, no study has been done so far that draws a direct correlation between these in-vitro observations and the biology of the pathogen in-vivo. The main goals of this study were to characterize the pathogenesis-associated functions of pgtE and study its role in the intracellular survival and in-vivo virulence of Salmonella Typhimurium. Our study elucidated a possible role of Salmonella Typhimurium pgtE in combating host antimicrobial peptide- bactericidal/ permeability increasing protein (BPI) to survive in human macrophages. The pgtE-deficient strain of Salmonella showed attenuated proliferation and enhanced colocalization with BPI in U937 and Thp1 cells. In the presence of polymixin B, the attenuated in-vitro survival of STM ΔpgtE suggested a role of PgtE against the antimicrobial peptides. In addition, our study revealed that compared to the wild type Salmonella, the pgtE mutant is replication-deficient in C57BL/6 mice. Further, we showed that PgtE interacts directly with several antimicrobial peptides (AMPs) in the host gut. This gives the pathogen a survival advantage and helps to mount a successful infection in the host.

Identification of Probucol as a candidate for combination therapy with Metformin for Type 2 diabetes

Type 2 Diabetes (T2D) is often managed with metformin as the drug of choice. While it is effective overall, many patients progress to exhibit complications. Strategic drug combinations to tackle this problem would be useful. We constructed a genome-wide protein-protein interaction network capturing a global perspective of perturbations in diabetes by integrating T2D subjects' transcriptomic data. We computed a 'frequently perturbed subnetwork' in T2D that captures common perturbations across tissue types and mapped the possible effects of Metformin onto it. We then identified a set of remaining T2D perturbations and potential drug targets among them, related to oxidative stress and hypercholesterolemia. We then identified Probucol as the potential co-drug for adjunct therapy with Metformin and evaluated the efficacy of the combination in a rat model of diabetes. We find Metformin-Probucol at 5:0.5 mg/kg effective in restoring near-normal serum glucose, lipid, and cholesterol levels.

Profiling system-wide variations and similarities between rheumatic heart disease and acute rheumatic fever-A pilot analysis

Rheumatic heart disease (RHD) continues to affect developing countries with low income due to the lack of resources and effective diagnostic techniques. Understanding the genetic basis common to both the diseases and that of progression from its prequel disease state, acute rheumatic fever (ARF), would aid in developing predictive biomarkers and improving patient care. To gain system-wide molecular insights into possible causes for progression, in this pilot study, we collected blood transcriptomes from ARF (5) and RHD (5) patients. Using an integrated transcriptome and network analysis approach, we identified a subnetwork comprising the most significantly differentially expressed genes and most perturbed pathways in RHD compared to ARF. For example, the chemokine signaling pathway was seen to be upregulated, while tryptophan metabolism was found to be downregulated in RHD. The subnetworks of variation between the two conditions provide unbiased molecular-level insights into the host processes that may be linked with the progression of ARF to RHD, which has the potential to inform future diagnostics and therapeutic strategies. We also found a significantly raised neutrophil/lymphocyte ratio in both ARF and RHD cohorts. Activated neutrophils and inhibited Natural Killer cell gene signatures reflected the drivers of the inflammatory process typical to both disease conditions.

In-silico study of influence of HLA heterogeneity on CTL responses across ethnicities to SARS-CoV-2

Differences in outcome to COVID-19 infection in different individuals is largely attributed to genetic heterogeneity leading to differential immune responses across individuals and populations. HLA is one such genetic factor that varies across individuals leading to differences in how T-cell responses are triggered against SARS-CoV-2, directly influencing disease susceptibility. HLA alleles that influence COVID-19 outcome, by virtue of epitope binding and presentation, have been identified in cohorts worldwide. However, the heterogeneity in HLA distribution across ethnic groups limits the generality of such association. In this study, we address this limitation by comparing the recognition of CTL epitopes across HLA genotypes and ethnic groups. Using HLA allele frequency data for ethnic groups from Allele Frequency Net Database (AFND), we construct synthetic populations for each ethnic group and show that CTL epitope strength varies across HLA genotypes and populations. We also observe that HLA genotypes, in certain cases, can have high CTL epitope strengths in the absence of top-responsive HLA alleles. Finally, we show that the theoretical estimate of responsiveness and hence protection offered by a HLA allele is bound to vary across ethnic groups, due to the influence of other HLA alleles within the HLA genotype on CTL epitope recognition. This emphasizes the need for studying HLA-disease associations at the genotype level rather than at a single allele level.

Personalized quantitative models of NAD metabolism in hepatocellular carcinoma identify a subgroup with poor prognosis

Cancer cells are known to undergo metabolic adaptation to cater to their enhanced energy demand. Nicotinamide adenine dinucleotide (NAD) is an essential metabolite regulating many cellular processes within the cell. The enzymes required for NAD synthesis, starting from the base precursor - tryptophan, are expressed in the liver and the kidney, while all other tissues convert NAD from intermediate precursors. The liver, being an active metabolic organ, is a primary contributor to NAD biosynthesis. Inhibition of key enzymes in the NAD biosynthetic pathways is proposed as a strategy for designing anti-cancer drugs. On the other hand, NAD supplementation has also been reported to be beneficial in cancer in some cases. As metabolic adaptation that occurs in cancer cells can lead to perturbations to the pathways, it is important to understand the exact nature of the perturbation in each individual patient. To investigate this, we use a mathematical modelling approach integrated with transcriptomes of patient samples from the TCGA-LIHC cohort. Quantitative profiling of the NAD biosynthesis pathway helps us understand the NAD biosynthetic status and changes in the controlling steps of the pathway. Our results indicate that NAD biosynthesis is heterogeneous among liver cancer patients, and that Nicotinate phosphoribosyl transferase (NAPRT) levels are indicative of the NAD biosynthetic status. Further, we find that reduced NAPRT levels combined with reduced Nicotinamide phosphoribosyl transferase (NAMPT) levels contribute to poor prognosis. Identification of the precise subgroup who may benefit from NAD supplementation in subgroup with low levels of NAPRT and NAMPT could be explored to improve patient outcome.

Fast Local Alignment of Protein Pockets (FLAPP): A System-Compiled Program for Large-Scale Binding Site Alignment

Protein function is a direct consequence of its sequence, structure, and the arrangement at the binding site. Bioinformatics using sequence analysis is typically used to gain a first insight into protein function. Protein structures, on the other hand, provide a higher resolution platform into understanding functions. As the protein structural information is increasingly becoming available through experimental structure determination and through advances in computational methods for structure prediction, the opportunity to utilize these data is also increasing. Structural analysis of small molecule ligand binding sites in particular provides a direct and more accurate window to infer protein function. However, it remains a poorly utilized resource due to the huge computational cost of existing methods that make large-scale structural comparisons of binding sites prohibitive. Here, we present an algorithm called FLAPP that produces very rapid atomic level alignments. By combining clique matching in graphs and the power of modern CPU architectures, FLAPP aligns a typical pair of binding sites at ∼12.5 ms using a single CPU core, ∼1 ms using 12 cores on a standard desktop machine, and performs a PDB-wide scan in 1-2 min. We perform rigorous validation of the algorithm at multiple levels of complexity and show that FLAPP provides accurate alignments. We also present a case study involving vitamin B12 binding sites to showcase the usefulness of FLAPP for performing an exhaustive alignment-based PDB-wide scan. We expect that this tool will be invaluable to the scientific community to quickly align millions of site pairs on a normal desktop machine to gain insights into protein function and drug discovery for drug target and off-target identification and polypharmacology.

Functional and Biochemical Characterization of the MazEF6 Toxin-Antitoxin System of Mycobacterium tuberculosis

The Mycobacterium tuberculosis genome harbors nine toxin-antitoxin (TA) systems that are members of the mazEF family, unlike other prokaryotes, which have only one or two. Although the overall tertiary folds of MazF toxins are predicted to be similar, it is unclear how they recognize structurally different RNAs and antitoxins with divergent sequence specificity. Here, we have expressed and purified the individual components and complex of the MazEF6 TA system from M. tuberculosis. Size exclusion chromatography-multiangle light scattering (SEC-MALS) was performed to determine the oligomerization status of the toxin, antitoxin, and the complex in different stoichiometric ratios. The relative stabilities of the proteins were determined by nano-differential scanning fluorimetry (nano-DSF). Microscale thermophoresis (MST) and yeast surface display (YSD) were performed to measure the relative affinities between the cognate toxin-antitoxin partners. The interaction between MazEF6 complexes and cognate promoter DNA was also studied using MST. Analysis of paired-end RNA sequencing data revealed that the overexpression of MazF6 resulted in differential expression of 323 transcripts in M. tuberculosis. Network analysis was performed to identify the nodes from the top-response network. The analysis of mRNA protection ratios resulted in identification of putative MazF6 cleavage site in its native host, M. tuberculosis. IMPORTANCE M. tuberculosis harbors a large number of type II toxin-antitoxin (TA) systems, the exact roles for most of which are unclear. Prior studies have reported that overexpression of several of these type II toxins inhibits bacterial growth and contributes to the formation of drug-tolerant populations in vitro. To obtain insights into M. tuberculosis MazEF6 type II TA system function, we determined stability, oligomeric states, and binding affinities of cognate partners with each other and with their promoter operator DNA. Using RNA-seq data obtained from M. tuberculosis overexpression strains, we have identified putative MazF6 cleavage sites and targets in its native, cellular context.

Mycobacterium tuberculosis requires SufT for Fe-S cluster maturation, metabolism, and survival in vivo

Iron-sulfur (Fe-S) cluster proteins carry out essential cellular functions in diverse organisms, including the human pathogen Mycobacterium tuberculosis (Mtb). The mechanisms underlying Fe-S cluster biogenesis are poorly defined in Mtb. Here, we show that Mtb SufT (Rv1466), a DUF59 domain-containing essential protein, is required for the Fe-S cluster maturation. Mtb SufT homodimerizes and interacts with Fe-S cluster biogenesis proteins; SufS and SufU. SufT also interacts with the 4Fe-4S cluster containing proteins; aconitase and SufR. Importantly, a hyperactive cysteine in the DUF59 domain mediates interaction of SufT with SufS, SufU, aconitase, and SufR. We efficiently repressed the expression of SufT to generate a SufT knock-down strain in Mtb (SufT-KD) using CRISPR interference. Depleting SufT reduces aconitase's enzymatic activity under standard growth conditions and in response to oxidative stress and iron limitation. The SufT-KD strain exhibited defective growth and an altered pool of tricarboxylic acid cycle intermediates, amino acids, and sulfur metabolites. Using Seahorse Extracellular Flux analyzer, we demonstrated that SufT depletion diminishes glycolytic rate and oxidative phosphorylation in Mtb. The SufT-KD strain showed defective survival upon exposure to oxidative stress and nitric oxide. Lastly, SufT depletion reduced the survival of Mtb in macrophages and attenuated the ability of Mtb to persist in mice. Altogether, SufT assists in Fe-S cluster maturation and couples this process to bioenergetics of Mtb for survival under low and high demand for Fe-S clusters.

A new blood-based RNA signature (R9), for monitoring effectiveness of tuberculosis treatment in a South Indian longitudinal cohort

Tuberculosis (TB) treatment involves a multidrug regimen for six months, and until two months, it is unclear if treatment is effective. This delay can lead to the evolution of drug resistance, lung damage, disease spread, and transmission. We identify a blood-based 9-gene signature using a computational pipeline that constructs and interrogates a genome-wide transcriptome-integrated protein-interaction network. The identified signature is able to determine treatment response at week 1-2 in three independent public datasets. Signature-based R9-score correctly detected treatment response at individual timepoints (204 samples) from a newly developed South Indian longitudinal cohort involving 32 patients with pulmonary TB. These results are consistent with conventional clinical metrics and can discriminate good from poor treatment responders at week 2 (AUC 0.93(0.81-1.00)). In this work, we provide proof of concept that the R9-score can determine treatment effectiveness, making a case for designing a larger clinical study.

SiteMotif: A graph-based algorithm for deriving structural motifs in Protein Ligand binding sites

Studying similarities in protein molecules has become a fundamental activity in much of biology and biomedical research, for which methods such as multiple sequence alignments are widely used. Most methods available for such comparisons cater to studying proteins which have clearly recognizable evolutionary relationships but not to proteins that recognize the same or similar ligands but do not share similarities in their sequence or structural folds. In many cases, proteins in the latter class share structural similarities only in their binding sites. While several algorithms are available for comparing binding sites, there are none for deriving structural motifs of the binding sites, independent of the whole proteins. We report the development of SiteMotif, a new algorithm that compares binding sites from multiple proteins and derives sequence-order independent structural site motifs. We have tested the algorithm at multiple levels of complexity and demonstrate its performance in different scenarios. We have benchmarked against 3 current methods available for binding site comparison and demonstrate superior performance of our algorithm. We show that SiteMotif identifies new structural motifs of spatially conserved residues in proteins, even when there is no sequence or fold-level similarity. We expect SiteMotif to be useful for deriving key mechanistic insights into the mode of ligand interaction, predict the ligand type that a protein can bind and improve the sensitivity of functional annotation.

A large number of biological functions are orchestrated by proteins. The function of proteins is governed by its structure and its interacting ligand. However, it is known that not all residues are involved in ligand recognition. More specifically, residues that are located within 4.5 Å of ligand atoms are considered to be ’binding sites’. Here, we have developed an algorithm called SiteMotif that efficiently aligns multiple binding sites into a common frame. This process enables us to derive conservation among the binding site residues in a sequence order independent manner. The algorithm was validated extensively across five different levels and measured binding site similarities in each of them. Previous research has found multiple instances where different proteins have comparable binding sites and hence perform the same function. We present the ability of our method to detect such scenarios. Finally, As a use case, we applied SiteMotif to a set of glutathione binding proteins and derived a site based sequence motif characteristic of all glutathione binding proteins.

A 9-gene biomarker panel identifies bacterial coinfections in culture-negative COVID-19 cases

Confirmatory diagnosis of bacterial coinfections with COVID-19 is challenging due to limited specificity of the gold-standard culture sensitivity test. This study presents a host gene signature to diagnose bacterial coinfection with high confidence.

Results of a nationally implemented cardiac screening programme in elite cricket players in England and Wales

OBJECTIVES

We assessed the diagnostic yield and costs of an electrocardiogram-based national screening programme in elite cricket players and the incremental value of transthoracic echocardiography and periodic evaluation.

DESIGN

Cross-sectional study.

METHODS

Between 2008 and 2019, 1208 cricketers underwent screening with a health questionnaire, 12-lead electrocardiogram and cardiology consultation. Athletes with concerning findings underwent on-site transthoracic echocardiography and further investigations as necessary. In addition, despite a normal health questionnaire and electrocardiogram, 342 (28.3%) athletes had a transthoracic echocardiogram and 493 (40.8%) underwent repeat evaluations.

RESULTS

After initial evaluation, 47 (3.9%) athletes underwent on-site transthoracic echocardiography of whom 35 (2.8%) were referred for further evaluation. Four athletes (0.3%) were diagnosed with major cardiac conditions; hypertrophic cardiomyopathy (n = 1), arrhythmogenic cardiomyopathy (n = 1) and Wolff-Parkinson-White pattern (n = 2). Two athletes were identified with minor valvular abnormalities. Repeat evaluation of 493 athletes identified hypertrophic cardiomyopathy in a 22-year-old athlete, two years after his initial normal screening. During a follow-up of 5.8 ± 2.9 years no additional diagnoses or adverse cardiac events were reported. The cost of the electrocardiogram-based programme was £127,844, translating to £106 per athlete and £25,569 per major cardiac condition identified.Routine transthoracic echocardiography in 342 athletes identified two athletes with major cardiac conditions (bicuspid aortic valve with severe aortopathy and aortic regurgitation and an atrial septal defect associated with right ventricular volume overload) and 10 athletes with minor abnormalities.

CONCLUSIONS

An electrocardiogram-based national screening programme identified a major cardiac condition in 0.3% of athletes. Routine transthoracic echocardiography and periodic evaluation increased the diagnostic yield to 0.6%, at an incremental cost.

Competing risks survival data under middle censoring-An application to COVID-19 pandemic

Survival data is being analysed here under the middle censoring scheme, using specifically quantile function modelling under competing risks. The use of middle censoring scheme has been shown to be very appropriate under the COVID-19 pandemic scenario. Cause-specific quantile inference under middle censoring is employed. Such quantile inferences are obtained through cumulative incidence function based on cause-specific proportional hazards model. The baseline lifetime is assumed to follow a very general parametric model namely the Weibull distribution, and is independent of the censoring mechanism. We obtain estimates of the unknown parameters and cause specific quantile functions under classical as well as a Bayesian set-up. A Monte Carlo simulation study assesses the relative performance of the different estimators. Finally, a real life data analysis is given for illustration of the proposed methods.

Cyclic di-GMP sensing histidine kinase PdtaS controls mycobacterial adaptation to carbon sources

Cell signaling relies on second messengers to transduce signals from the sensory apparatus to downstream signaling pathway components. In bacteria, one of the most important and ubiquitous second messenger is the small molecule cyclic diguanosine monophosphate (c-di-GMP). While the biosynthesis, degradation, and regulatory pathways controlled by c-di-GMP are well characterized, the mechanisms through which c-di-GMP controls these processes are not entirely understood. Herein we present the report of a c-di-GMP sensing sensor histidine kinase PdtaS (Rv3220c), which binds to c-di-GMP at submicromolar concentrations, subsequently perturbing signaling of the PdtaS-PdtaR (Rv1626) two-component system. Aided by biochemical analysis, genetics, molecular docking, FRET microscopy, and structural modelling, we have characterized the binding of c-di-GMP in the GAF domain of PdtaS. We show that a pdtaS knockout in Mycobacterium smegmatis is severely compromised in growth on amino acid deficient media and exhibits global transcriptional dysregulation. The perturbation of the c-di-GMP-PdtaS-PdtaR axis results in a cascade of cellular changes recorded by a multiparametric systems' approach of transcriptomics, unbiased metabolomics, and lipid analyses.