The exostosin glycosyltransferase 1/STAT3 axis is a driver of breast cancer aggressiveness.

The epithelial-mesenchymal transition (EMT) program is crucial for transforming carcinoma cells into a partially mesenchymal state, enhancing their chemoresistance, migration, and metastasis. This shift in cell state is tightly regulated by cellular mechanisms that are not yet fully characterized. One intriguing EMT aspect is the rewiring of the proteoglycan landscape, particularly the induction of heparan sulfate proteoglycan (HSPG) biosynthesis. This proteoglycan functions as a co-receptor that accelerates cancer-associated signaling pathways through its negatively-charged residues. However, the precise mechanisms through which EMT governs HSPG biosynthesis and its role in cancer cell plasticity remain elusive. Here, we identified exostosin glycosyltransferase 1 (EXT1), a central enzyme in HSPG biosynthesis, to be selectively upregulated in aggressive tumor subtypes and cancer cell lines, and to function as a key player in breast cancer aggressiveness. Notably, ectopic expression of EXT1 in epithelial cells is sufficient to induce HSPG levels and the expression of known mesenchymal markers, subsequently enhancing EMT features, including cell migration, invasion, and tumor formation. Additionally, EXT1 loss in MDA-MB-231 cells inhibits their aggressiveness-associated traits such as migration, chemoresistance, tumor formation, and metastasis. Our findings reveal that EXT1, through its role in HSPG biosynthesis, governs signal transducer and activator of transcription 3 (STAT3) signaling, a known regulator of cancer cell aggressiveness. Collectively, we present the EXT1/HSPG/STAT3 axis as a central regulator of cancer cell plasticity that directly links proteoglycan synthesis to oncogenic signaling pathways.

Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition.

Exploring the complexity of the epithelial-to-mesenchymal transition (EMT) unveils a diversity of potential cell fates; however, the exact timing and mechanisms by which early cell states diverge into distinct EMT trajectories remain unclear. Studying these EMT trajectories through single-cell RNA sequencing is challenging due to the necessity of sacrificing cells for each measurement. In this study, we employed optimal-transport analysis to reconstruct the past trajectories of different cell fates during TGF-beta-induced EMT in the MCF10A cell line. Our analysis revealed three distinct trajectories leading to low EMT, partial EMT, and high EMT states. Cells along the partial EMT trajectory showed substantial variations in the EMT signature and exhibited pronounced stemness. Throughout this EMT trajectory, we observed a consistent downregulation of the EED and EZH2 genes. This finding was validated by recent inhibitor screens of EMT regulators and CRISPR screen studies. Moreover, we applied our analysis of early-phase differential gene expression to gene sets associated with stemness and proliferation, pinpointing ITGB4, LAMA3, and LAMB3 as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that CENPF, CKS1B, and MKI67 showed significant upregulation in the high EMT trajectory. While the first group of genes aligns with findings from previous studies, our work uniquely pinpoints the precise timing of these upregulations. Finally, the identification of the latter group of genes sheds light on potential cell cycle targets for modulating EMT trajectories.

Perspectives on polarity - exploring biological asymmetry across scales.

In this Perspective, Journal of Cell Science invited researchers working on cell and tissue polarity to share their thoughts on unique, emerging or open questions relating to their field. The goal of this article is to feature 'voices' from scientists around the world and at various career stages, to bring attention to innovative and thought-provoking topics of interest to the cell biology community. These voices discuss intriguing questions that consider polarity across scales, evolution, development and disease. What can yeast and protists tell us about the evolution of cell and tissue polarity in animals? How are cell fate and development influenced by emerging dynamics in cell polarity? What can we learn from atypical and extreme polarity systems? How can we arrive at a more unified biophysical understanding of polarity? Taken together, these pieces demonstrate the broad relevance of the fascinating phenomenon of cell polarization to diverse fundamental biological questions.

p53 amyloid pathology is correlated with higher cancer grade irrespective of the mutant or wild-type form.

p53 (also known as TP53) mutation and amyloid formation are long associated with cancer pathogenesis; however, the direct demonstration of the link between p53 amyloid load and cancer progression is lacking. Using multi-disciplinary techniques and 59 tissues (53 oral and stomach cancer tumor tissue samples from Indian individuals with cancer and six non-cancer oral and stomach tissue samples), we showed that p53 amyloid load and cancer grades are highly correlated. Furthermore, next-generation sequencing (NGS) data suggest that not only mutant p53 (e.g. single-nucleotide variants, deletions, and insertions) but wild-type p53 also formed amyloids either in the nucleus (50%) and/or in the cytoplasm in most cancer tissues. Interestingly, in all these cancer tissues, p53 displays a loss of DNA-binding and transcriptional activities, suggesting that the level of amyloid load correlates with the degree of loss and an increase in cancer grades. The p53 amyloids also sequester higher amounts of the related p63 and p73 (also known as TP63 and TP73, respectively) protein in higher-grade tumor tissues. The data suggest p53 misfolding and/or aggregation, and subsequent amyloid formation, lead to loss of the tumor-suppressive function and the gain of oncogenic function, aggravation of which might determine the cancer grade.

Controlling Umklapp Scattering in a Bilayer Graphene Moiré Superlattice.

We present experimental findings on electron-electron scattering in two-dimensional moiré heterostructures with a tunable Fermi wave vector, reciprocal lattice vector, and band gap. We achieve this in high-mobility aligned heterostructures of bilayer graphene (BLG) and hBN. Around the half-full point, the primary contribution to the resistance of these devices arises from Umklapp electron-electron (Uee) scattering, making the resistance of graphene/hBN moiré devices significantly larger than that of non-aligned devices (where Uee is forbidden). We find that the strength of Uee scattering follows a universal scaling with Fermi energy and is nonmonotonically dependent on the superlattice period. The Uee scattering can be tuned with the electric field and is affected by layer polarization of BLG. It has a strong particle-hole asymmetry; the resistance when the chemical potential is in the conduction band is significantly lower than when it is in the valence band, making the electron-doped regime more practical for potential applications.

Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity.

Phenotypic plasticity was recently incorporated as a hallmark of cancer. This plasticity can manifest along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. In particular, the knowledge necessary for a predictive understanding of how individual cancer cells and populations of cells dynamically switch their phenotypes in response to the intensity and/or duration of their current and past environmental stimuli remains far from complete. Here, we present recent investigations of phenotypic plasticity from a systems-level perspective using two exemplars: epithelial-mesenchymal plasticity in carcinomas and phenotypic switching in melanoma. We highlight how an integrated computational-experimental approach has helped unravel insights into specific dynamical hallmarks of phenotypic plasticity in different cancers to address the following questions: a) how many distinct cell-states or phenotypes exist?; b) how reversible are transitions among these cell-states, and what factors control the extent of reversibility?; and c) how might cell-cell communication be able to alter rates of cell-state switching and enable diverse patterns of phenotypic heterogeneity? Understanding these dynamic features of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach.

Spatial heterogeneity in tumor adhesion qualifies collective cell invasion.

Collective cell invasion (CCI), a canon of most invasive solid tumors, is an emergent property of the interactions between cancer cells and their surrounding extracellular matrix (ECM). However, tumor populations invariably consist of cells expressing variable levels of adhesive proteins that mediate such interactions, disallowing an intuitive understanding of how tumor invasiveness at a multicellular scale is influenced by spatial heterogeneity of cell-cell and cell-ECM adhesion. Here, we have used a Cellular Potts model-based multiscale computational framework that is constructed on the histopathological principles of glandular cancers. In earlier efforts on homogenous cancer cell populations, this framework revealed the relative ranges of interactions, including cell-cell and cell-ECM adhesion that drove collective, dispersed, and mixed multimodal invasion. Here, we constitute a tumor core of two separate cell subsets showing distinct intra- and inter-subset cell-cell or cell-ECM adhesion strengths. These two subsets of cells are arranged to varying extents of spatial intermingling, which we call the heterogeneity index (HI). We observe that low and high inter-subset cell adhesion favors invasion of high-HI and low-HI intermingled populations with distinct intra-subset cell-cell adhesion strengths, respectively. In addition, for explored values of cell-ECM adhesion strengths, populations with high HI values collectively invade better than those with lower HI values. We then asked how spatial invasion is regulated by progressively intermingled cellular subsets that are epithelial, i.e., showed high cell-cell but poor cell-ECM adhesion, and mesenchymal, i.e., with reversed adhesion strengths to the former. Here too, inter-subset adhesion plays an important role in contextualizing the proportionate relationship between HI and invasion. An exception to this relationship is seen for cases of heterogeneous cell-ECM adhesion where sub-maximal HI patterns with higher outer localization of cells with stronger ECM adhesion collectively invade better than their relatively higher-HI counterparts. Our simulations also reveal how adhesion heterogeneity qualifies collective invasion, when either cell-cell or cell-ECM adhesion type is varied but results in an invasive dispersion when both adhesion types are simultaneously altered.

Oncogenic gain of function due to p53 amyloids occurs through aberrant alteration of cell cycle and proliferation.

Transcription factor p53 (also known as TP53) has been shown to aggregate into cytoplasmic and nuclear inclusions, compromising its native tumor suppressive functions. Recently, p53 has been shown to form amyloids, which play a role in conferring cancerous properties to cells, leading to tumorigenesis. However, the exact pathways involved in p53 amyloid-mediated cellular transformations are unknown. Here, using an in cellulo model of full-length p53 amyloid formation, we demonstrate the mechanism of loss of p53 tumor-suppressive function with concomitant oncogenic gain of functions. Global gene expression profiling of cells suggests that p53 amyloid formation dysregulates genes associated with the cell cycle, proliferation, apoptosis and senescence along with major signaling pathways. This is further supported by a proteome analysis, showing a significant alteration in levels of p53 target proteins and enhanced metabolism, which enables the survival of cells. Our data indicate that specifically targeting the key molecules in pathways affected by p53 amyloid formation, such as cyclin-dependent kinase-1, leads to loss of the oncogenic phenotype and induces apoptosis of cells. Overall, our work establishes the mechanism of the transformation of cells due to p53 amyloids leading to cancer pathogenesis. This article has an associated First Person interview with the first author of the paper.

Whole genome sequencing of families diagnosed with cardiac channelopathies reveals structural variants missed by whole exome sequencing.

Cardiac channelopathies are a group of heritable disorders that affect the heart's electrical activity due to genetic variations present in genes coding for ion channels. With the advent of new sequencing technologies, molecular diagnosis of these disorders in patients has paved the way for early identification, therapeutic management and family screening. The objective of this retrospective study was to understand the efficacy of whole-genome sequencing in diagnosing patients with suspected cardiac channelopathies who were reported negative after whole exome sequencing and analysis. We employed a 3-tier analysis approach to identify nonsynonymous variations and loss-of-function variations missed by exome sequencing, and structural variations that are better resolved only by sequencing whole genomes. By performing whole genome sequencing and analyzing 25 exome-negative cardiac channelopathy patients, we identified 3 pathogenic variations. These include a heterozygous likely pathogenic nonsynonymous variation, CACNA1C:NM_000719:exon19:c.C2570G:p. P857R, which causes autosomal dominant long QT syndrome in the absence of Timothy syndrome, a heterozygous loss-of-function variation CASQ2:NM_001232.4:c.420+2T>C classified as pathogenic, and a 9.2 kb structural variation that spans exon 2 of the KCNQ1 gene, which is likely to cause Jervell-Lange-Nielssen syndrome. In addition, we also identified a loss-of-function variation and 16 structural variations of unknown significance (VUS). Further studies are required to elucidate the role of these identified VUS in gene regulation and decipher the underlying genetic and molecular mechanisms of these disorders. Our present study serves as a pilot for understanding the utility of WGS over clinical exomes in diagnosing cardiac channelopathy disorders.

Intrinsically Disordered Proteins: Critical Components of the Wetware.

Despite the wealth of knowledge gained about intrinsically disordered proteins (IDPs) since their discovery, there are several aspects that remain unexplored and, hence, poorly understood. A living cell is a complex adaptive system that can be described as a wetware─a metaphor used to describe the cell as a computer comprising both hardware and software and attuned to logic gates─capable of "making" decisions. In this focused Review, we discuss how IDPs, as critical components of the wetware, influence cell-fate decisions by wiring protein interaction networks to keep them minimally frustrated. Because IDPs lie between order and chaos, we explore the possibility that they can be modeled as attractors. Further, we discuss how the conformational dynamics of IDPs manifests itself as conformational noise, which can potentially amplify transcriptional noise to stochastically switch cellular phenotypes. Finally, we explore the potential role of IDPs in prebiotic evolution, in forming proteinaceous membrane-less organelles, in the origin of multicellularity, and in protein conformation-based transgenerational inheritance of acquired characteristics. Together, these ideas provide a new conceptual framework to discern how IDPs may perform critical biological functions despite their lack of structure.

Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes.

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.

Identification of EMT signaling cross-talk and gene regulatory networks by single-cell RNA sequencing.

The epithelial-to-mesenchymal transition (EMT) plays a critical role during normal development and in cancer progression. EMT is induced by various signaling pathways, including TGF-ß, BMP, Wnt-ß-catenin, NOTCH, Shh, and receptor tyrosine kinases. In this study, we performed single-cell RNA sequencing on MCF10A cells undergoing EMT by TGF-ß1 stimulation. Our comprehensive analysis revealed that cells progress through EMT at different paces. Using pseudotime clustering reconstruction of gene-expression profiles during EMT, we found sequential and parallel activation of EMT signaling pathways. We also observed various transitional cellular states during EMT. We identified regulatory signaling nodes that drive EMT with the expression of important microRNAs and transcription factors. Using a random circuit perturbation methodology, we demonstrate that the NOTCH signaling pathway acts as a key driver of TGF-ß-induced EMT. Furthermore, we demonstrate that the gene signatures of pseudotime clusters corresponding to the intermediate hybrid EMT state are associated with poor patient outcome. Overall, this study provides insight into context-specific drivers of cancer progression and highlights the complexities of the EMT process.

Total hip arthroplasty in active and advanced tubercular arthritis: a systematic review of the current evidence.

STUDY DESIGN: Systematic review. INTRODUCTION: Total hip arthroplasty (THA) is a well-acknowledged surgical intervention to restore a painless and mobile joint in patients with osteoarticular tubercular arthritis of the hip joint. However, there is still substantial uncertainty about the ideal management, clinical and functional outcomes following THA undertaken in patients with acute Mycobacterium tuberculosis (TB) hip infections. AIM OF THE STUDY: To undertake a systematic review and evaluate existing literature on patients undergoing THA for acute mycobacterium tuberculosis arthritis of the hip. METHODS: A systematic review of electronic databases of PubMed, EMBASE, Scopus, Web of Science and Cochrane Library was performed on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search focused on "arthroplasty in cases with tuberculosis of hip joint" since inception of databases until July 2023. Data on patient demographics, clinical characteristics, treatment administered, surgical interventions and outcome, as reported in the included studies, were recorded. Median (range) and mean (standard deviation) were used to summarise the data for continuous variables (as reported in the original studies); and frequency/percentage was employed for categorical variables. Available data on Harris hip scores and complications were statistically pooled using random-effects meta-analysis or fixed-effect meta-analysis, as appropriate RESULTS: Among a total of 1695 articles, 15 papers were selected for qualitative summarisation and 12 reporting relevant data were included for proportional meta-analysis. A total of 303 patients (mean age: 34 to 52 years; mean follow-up: 2.5 to 10.5 years) were included in our systematic review. In a majority of included studies, postero-lateral approach and non-cemented prosthesis were employed. Fourteen studies described a single-staged procedure in the absence of sinus, abscess and tubercular infection syndrome (TIS). All surgeries were performed under cover of prolonged course of multi-drug anti-tubercular regimen. The mean Harris hip score (HHS) at final follow-up was 91.36 [95% confidence interval (CI): 89.56-93.16; I2:90.44%; p<0.001]. There were 30 complications amongst 174 (9.9%) patients (95% CI: 0.06-0.13; p=0.14; I2=0%). CONCLUSION: THA is a safe and effective surgical intervention in patients with active and advanced TB arthritis of hip. It is recommended that the surgery be performed under cover of multi-drug anti-tubercular regimen. In patients with active sinus tracts, abscesses and TIS, surgery may be accomplished in a multi-staged manner. The clinical (range of motion, deformity correction, walking ability and pain scores), radiological (evidence of radiological reactivation and implant incorporation) and function outcome (as assessed by HHS) significantly improve after THA in these patients.

Effectiveness of AI-powered Chatbots in responding to orthopaedic postgraduate exam questions-an observational study.

PURPOSE: This study analyses the performance and proficiency of the three Artificial Intelligence (AI) generative chatbots (ChatGPT-3.5, ChatGPT-4.0, Bard Google AI®) and in answering the Multiple Choice Questions (MCQs) of postgraduate (PG) level orthopaedic qualifying examinations. METHODS: A series of 120 mock Single Best Answer' (SBA) MCQs with four possible options named A, B, C and D as answers on various musculoskeletal (MSK) conditions covering Trauma and Orthopaedic curricula were compiled. A standardised text prompt was used to generate and feed ChatGPT (both 3.5 and 4.0 versions) and Google Bard programs, which were then statistically analysed. RESULTS: Significant differences were found between responses from Chat GPT 3.5 with Chat GPT 4.0 (Chi square = 27.2, P < 0.001) and on comparing both Chat GPT 3.5 (Chi square = 63.852, P < 0.001) with Chat GPT 4.0 (Chi square = 44.246, P < 0.001) with. Bard Google AI® had 100% efficiency and was significantly more efficient than both Chat GPT 3.5 with Chat GPT 4.0 (p < 0.0001). CONCLUSION: The results demonstrate the variable potential of the different AI generative chatbots (Chat GPT 3.5, Chat GPT 4.0 and Bard Google) in their ability to answer the MCQ of PG-level orthopaedic qualifying examinations. Bard Google AI® has shown superior performance than both ChatGPT versions, underlining the potential of such large language processing models in processing and applying orthopaedic subspecialty knowledge at a PG level.

Emerging perspectives on growth factor metabolic relationships in the ovarian cancer ascites environment.

The ascites ecosystem in ovarian cancer is inhabited by complex cell types and is bathed in an environment rich in cytokines, chemokines, and growth factors that directly and indirectly impact metabolism of cancer cells and tumor associated cells. This milieu of malignant ascites, provides a 'rich' environment for the disease to thrive, contributing to every aspect of advanced ovarian cancer, a devastating gynecological cancer with a significant gap in targeted therapeutics. In this perspective we focus our discussions on the 'acellular' constituents of this liquid malignant tumor microenvironment, and how they influence metabolic pathways. Growth factors, chemokines and cytokines are known modulators of metabolism and have been shown to impact nutrient uptake and metabolic flexibility of tumors, yet few studies have explored how their enrichment in malignant ascites of ovarian cancer patients contributes to the metabolic requirements of ascites-resident cells. We focus here on TGF-ßs, VEGF and ILs, which are frequently elevated in ovarian cancer ascites and have all been described to have direct or indirect effects on metabolism, often through gene regulation of metabolic enzymes. We summarize what is known, describe gaps in knowledge, and provide examples from other tumor types to infer potential unexplored roles and mechanisms for ovarian cancer. The distribution and variation in acellular ascites components between patients poses both a challenge and opportunity to further understand how the ascites may contribute to disease heterogeneity. The review also highlights opportunities for studies on ascites-derived factors in regulating the ascites metabolic environment that could act as a unique signature in aiding clinical decisions in the future.

Effects of microRNA-mediated negative feedback on gene expression noise.

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally in eukaryotes by binding with target mRNAs and preventing translation. miRNA-mediated feedback motifs are ubiquitous in various genetic networks that control cellular decision making. A key question is how such a feedback mechanism may affect gene expression noise. To answer this, we have developed a mathematical model to study the effects of a miRNA-dependent negative-feedback loop on mean expression and noise in target mRNAs. Combining analytics and simulations, we show the existence of an expression threshold demarcating repressed and expressed regimes in agreement with earlier studies. The steady-state mRNA distributions are bimodal near the threshold, where copy numbers of mRNAs and miRNAs exhibit enhanced anticorrelated fluctuations. Moreover, variation of negative-feedback strength shifts the threshold locations and modulates the noise profiles. Notably, the miRNA-mRNA binding affinity and feedback strength collectively shape the bimodality. We also compare our model with a direct auto-repression motif, where a gene produces its own repressor. Auto-repression fails to produce bimodal mRNA distributions as found in miRNA-based indirect repression, suggesting the crucial role of miRNAs in creating phenotypic diversity. Together, we demonstrate how miRNA-dependent negative feedback modifies the expression threshold and leads to a broader parameter regime of bimodality compared to the no-feedback case.

Unique sphingolipid signature identifies luminal and triple-negative breast cancer subtypes.

Breast cancer (luminal and triple-negative breast cancer [TNBC]) is the most common cancer among women in India and worldwide. Altered sphingolipid levels have emerged as a common phenomenon during cancer progression. However, these alterations are yet to be translated into robust diagnostic and prognostic markers for cancer. Here, we present the quantified sphingolipids of tumor and adjacent-normal tissues from patients of luminal (n = 70) and TNBC (n = 42) subtype from an Indian cohort using targeted liquid chromatography mass spectrometry. We recorded unique sphingolipid profiles that distinguished luminal and TNBC tumors in comparison to adjacent normal tissue by six-sphingolipid signatures. Moreover, systematic comparison of the profiles of luminal and TNBC tumors provided a unique five-sphingolipid signature distinguishing the two subtypes. We further identified key sphingolipids that can stratify grade II and grade III tumors of luminal and TNBC subtype as well as their lymphovascular invasion status. Therefore, we provide the right evidence to develop these candidate sphingolipids as widely acceptable marker/s capable of diagnosing luminal vs TNBC subtype of breast cancer, and predicting the disease severity by identifying the tumor grade.

Theoretical and computational tools to model multistable gene regulatory networks.

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.

Whole-genome sequencing of 1029 Indian individuals reveals unique and rare structural variants.

Structural variants contribute to genetic variability in human genomes and they can be presented in population-specific patterns. We aimed to understand the landscape of structural variants in the genomes of healthy Indian individuals and explore their potential implications in genetic disease conditions. For the identification of structural variants, a whole genome sequencing dataset of 1029 self-declared healthy Indian individuals from the IndiGen project was analysed. Further, these variants were evaluated for potential pathogenicity and their associations with genetic diseases. We also compared our identified variations with the existing global datasets. We generated a compendium of total 38,560 high-confident structural variants, comprising 28,393 deletions, 5030 duplications, 5038 insertions, and 99 inversions. Particularly, we identified around 55% of all these variants were found to be unique to the studied population. Further analysis revealed 134 deletions with predicted pathogenic/likely pathogenic effects and their affected genes were majorly enriched for neurological disease conditions, such as intellectual disability and neurodegenerative diseases. The IndiGenomes dataset helped us to understand the unique spectrum of structural variants in the Indian population. More than half of identified variants were not present in the publicly available global dataset on structural variants. Clinically important deletions identified in IndiGenomes might aid in improving the diagnosis of unsolved genetic diseases, particularly in neurological conditions. Along with basal allele frequency data and clinically important deletions, IndiGenomes data might serve as a baseline resource for future studies on genomic structural variant analysis in the Indian population.

Clinical metabolomics by NMR revealed serum metabolic signatures for differentiating sarcoidosis from tuberculosis.

BACKGROUND: Pulmonary sarcoidosis (SAR) and tuberculosis (TB) are two granulomatous lung-diseases and often pose a diagnostic challenge to a treating physicians. OBJECTIVE: The present study aims to explore the diagnostic potential of NMR based serum metabolomics approach to differentiate SAR from TB. MATERIALS AND METHOD: The blood samples were obtained from three study groups: SAR (N = 35), TB (N = 28) and healthy normal subjects (NC, N = 56) and their serum metabolic profiles were measured using 1D 1H CPMG (Carr-Purcell-Meiboom-Gill) NMR spectra recorded at 800 MHz NMR spectrometer. The quantitative metabolic profiles were compared employing a combination of univariate and multivariate statistical analysis methods and evaluated for their diagnostic potential using receiver operating characteristic (ROC) curve analysis. RESULTS: Compared to SAR, the sera of TB patients were characterized by (a) elevated levels of lactate, acetate, 3-hydroxybutyrate (3HB), glutamate and succinate (b) decreased levels of glucose, citrate, pyruvate, glutamine, and several lipid and membrane metabolites (such as very-low/low density lipoproteins (VLDL/LDL), polyunsaturated fatty acids, etc.). CONCLUSION: The metabolic disturbances not only found to be well in concordance with various previous reports, these further demonstrated very high sensitivity and specificity to distinguish SAR from TB patients suggesting serum metabolomics analysis can serve as surrogate method in the diagnosis and clinical management of SAR.