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Ahmad, T.

Publications and source records attributed to Ahmad, T..

18 recordsLinked to original sources

Safe Redosable Low-Immunogenic In Vivo CAR-T Therapy for B Cell Malignancies and Solid Tumors

In vivo CAR-T cell therapy eliminates manufacturing complexities associated with ex vivo autologous approaches, but safety concerns have limited adoption. We developed viroVbot, a next-generation in vivo CAR-T platform, by combining computational immunogenicity prediction (CIMMEXTM) with envelope engineering. Screening 22,562 glycoprotein sequences, we identified 641 vesiculovirus homologs, from which we selected Piry virus glycoprotein (PIRYV) as the optimal candidate. PIRYV exhibited lower MHC-epitope density, reduced human seroprevalence, with decreased T cell activation compared to VSV-G. To enhance targeting specificity, we engineered receptor-binding-deficient PIRYV (ePIRYVRBD) displaying CD3/CD7 nanobodies for T cell-selective transduction. To maximize safety, we engineered CAR-TRAP producer cells to eliminate unwanted B cell transduction and incorporated machine learning-optimized T cell-specific promoters that restrict CAR activation exclusively to lymphocytes. Additional modifications suppressed hepatocyte expression and prevented phagocytic uptake. In humanized xenograft models, viroVbot3 generated potent BCMA/CD19 specific CAR-T responses against multiple myeloma and Claudin18.2-targeting gastric cancer, demonstrating sequential redosing with alternative envelopes. Critically, viroVbot3 exhibited minimal off-target organ biodistribution with CAR expression restricted to T lymphocytes. These findings establish viroVbot as a low-immunogenic platform for scalable in vivo CAR-T manufacturing with capability for sequential redosing across hematologic and solid tumors.

bioengineering↗

A complete human pancreatic cancer genome

Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine.1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions.1-3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres.4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

genomics↗

Reprogramming BCMA-Targeted CAR-T Cells through γ-Secretase Modulation Blocks Antigen Shedding and Extends CAR-T Longevity

B-cell maturation antigen (BCMA) shedding by {gamma}-secretase generates soluble BCMA (sBCMA), which diminishes membrane antigen density, and limits the durability of BCMA-directed immunotherapies in multiple myeloma (MM). Here, using AI-driven diffusion modeling, we identify peptide inhibitors that selectively block {gamma}-secretase-mediated BCMA cleavage, stabilizing membrane-bound BCMA (mBCMA) without compromising cellular viability. The lead peptide, P5, suppresses sBCMA and restores mBCMA in vitro and in xenograft models. To create sustained, cell-intrinsic inhibition, we engineered Shedding Deterrent Locked-in (SHEDLOCK) CAR-T cells that locally secrete {gamma}-secretase-modulatory peptides. SHEDLOCK-1 CAR-T cells secreting P5 exhibits enhanced cytotoxicity and persistence relative to conventional CAR-T cells. Building on this, SHEDLOCK-2 CAR-T cells were generated, which secrete a modified, naturally derived peptide (nxP) that directly engages the {gamma}-secretase catalytic site, concurrently preventing BCMA shedding, and surprisingly enhancing CAR-T cell longevity by preserving telomere integrity and metabolic fitness. In MM xenograft and patient-derived models, SHEDLOCK-2 CAR-T cells demonstrate durable antitumor activity with a favorable safety profile. Together, these findings establish SHEDLOCK as a next-generation CAR-T platform and provide a strong preclinical foundation for Phase I clinical evaluation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/700575v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@3cd38aorg.highwire.dtl.DTLVardef@164167borg.highwire.dtl.DTLVardef@1ffed21org.highwire.dtl.DTLVardef@1294d06_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

KDM7B-mediated demethylation of RNF113A regulates small cell lung cancer sensitivity to alkylation damage

Chemoresistance remains a major obstacle to effective cancer treatment, often driven by enhanced DNA repair mechanisms that enable tumor cells to withstand genotoxic therapies. One such pathway involves the atypical DNA damage repair complex ALKBH3-ASCC, activated by the E3 ligase RNF113A in response to alkylation damage. We previously showed that SMYD3-dependent methylation of RNF113A stimulates this pathway, enhancing DNA repair and promoting resistance. Here, we identify KDM7B/PHF8 as the bona fide RNF113A demethylase, establishing one of the first functional examples of a dynamic, reversible non-histone methylation event regulating genome integrity. KDM7B antagonizes SMYD3 activity by maintaining low levels of methylated RNF113A, thereby limiting ASCC activation and sensitizing cancer cells to alkylating agents. To dissect this regulation in depth, we focused on small cell lung cancer (SCLC), a particularly aggressive malignancy characterized by limited therapeutic options and rapid acquisition of resistance. In SCLC, high KDM7B levels correlate with improved patient prognosis, whereas xenografts with reduced expression exhibit diminished responses to alkylating treatment. Moreover, CRISPR-based on/off modulation of KDM7B in genetically engineered SCLC mouse models demonstrates its central role in determining tumor response to chemotherapy. Our findings position the RNF113A-ASCC axis as a central modulator of chemoresistance, regulated through a post-translational methylation switch representing an innovative therapeutic vulnerability that could be exploited to enhance the efficacy of alkylating agents. Targeting this pathway may provide new opportunities to overcome chemoresistance, with KDM7B levels serving as a predictive biomarker to guide treatment in SCLC.

cell biology↗

Long-read sequencing of single cell-derived melanoma subclones reveals divergent and parallel genomic and epigenomic evolutionary trajectories

Tumor evolution is driven by various mutational processes, ranging from single-nucleotide vari- ants (SNVs) to large structural variants (SVs) to dynamic shifts in DNA methylation. Current short-read sequencing methods struggle to accurately capture the full spectrum of these genomic and epigenomic alter- ations due to inherent technical limitations. To overcome that, here we introduce an approach for long-read sequencing of single-cell derived subclones, and use it to profile 23 subclones of a mouse melanoma cell line, characterized with distinct growth phenotypes and treatment responses. We develop a computational frame- work for harmonization and joint analysis of different variant types in the evolutionary context. Uniquely, our framework enables detection of recurrent amplifications of putative driver genes, generated by indepen- dent SVs across different lineages, suggesting parallel evolution. In addition, our approach revealed gradual and lineage-specific methylation changes associated with aggressive clonal phenotypes. We also show our set of phylogeny-constrained variant calls along with openly released sequencing data can be a valuable resource for the development of new computational methods.

genomics↗

AI-Guided Design and AKT3 Degradation Synergize to Enhance Bispecific and Trispecific CAR-T Cell Persistence and Overcome Antigen Escape

The structural design of chimeric antigen receptors (CARs) is critical for achieving robust and durable anti-tumor responses, particularly when targeting multiple antigens to prevent tumor antigen escape. However, increasing CAR complexity can introduce structural vulnerabilities, leading to antigen-independent T cell activation, activation-induced cell death, and reduced CAR-T cell persistence. To overcome these challenges, we designed 10,824 CAR molecules across diverse formats and screened 1,452 constructs in-vitro to develop an artificial intelligence model, termed CAR-Mediated Self-Destruction (CARMSeD), which predicts CAR designs susceptible to self-activation and dysfunction. Guided by CARMSeD and structural CAR-CAR interaction modeling, we identified optimized CAR architectures incorporating ICOS and 4-1BB co-stimulatory domains. Humanized bispecific CARs targeting CD20/CD19 and CD22/CD19 demonstrated superior anti-tumor efficacy and persistence both in-vitro and in various xenograft mice models. To further extend CAR-T cell persistence, we engineered bispecific CARs integrated with an AKT3-targeted PROTAC strategy. Targeted degradation of AKT3 enhanced anti-tumor potency, promoted memory T cell formation, and enabled sustained responses even under tumor rechallenge and CD19 antigen-loss conditions. Mechanistically, these effects were mediated by metabolic reprogramming involving FOXO4; notably, FOXO4-deficient CAR-T cells exhibited impaired long-term persistence. Leveraging these mechanistic insights, we developed a trispecific CAR-T cell platform incorporating a bispecific T cell engager (BiTE) targeting CD22/CD3, combined with AKT3 PROTACs. These trispecific CAR-T cells achieved potent tumor eradication, even against malignancies lacking both CD19 and CD20 expression. Collectively, this study presents a comprehensive strategy combining structure-based design, AI-guided screening, and targeted protein degradation to engineer next-generation bi and trispecific CAR-T cells with enhanced persistence, broad antigen coverage, and superior therapeutic durability.

cancer biology↗

Biofabrication of a filtration barrier by integrating electrospun membranes and flow in a glomerular co-culture

The glomerulus is the functional unit of the kidney, where urine is filtered from blood. This process happens through the glomerular filtration barrier (GFB) which is composed of glomerular endothelial cells, podocytes, and glomerular basement membrane (GBM). Damage to any component of GFB results in failure of the barriers function, causing proteinuria that can lead to end-stage kidney failure. There is a high need for reliable in vitro models of the GFB to study pathological conditions and to test potential novel therapeutic options. We established an artificial GBM generated by electrospinning of poly-L-lactic acid fibers that were coated with polydopamine and gelatin and seeded with human glomerular endothelial cells and podocytes onto different sides. The orientation of fibers in the artificial GBM, their surface chemistry and effects on glomerular cells were characterized in depth. Glomerular endothelial cells and podocytes, including hiPSC-derived podocytes formed monolayers on the artificial GBM and revealed cell type-specific marker expression and morphology. Cell-cell communication was possible between podocytes and glomerular endothelial cells in both directions though the artificial membrane. Different molecular dextrans showed size selective permeability of the ex vivo GFB model. Introduction of shear stress by applying flow with a 3D printed micro-bioreactor improved cellular ultrastructure with formation of glomerular endothelial cell fenestrae-like structures and long podocyte foot process-like protrusions that both are usually absent in other in vitro models. Personalized hiPSC-derived podocytes within our model will allow to study the role of patient-specific podocyte mutations or individual treatment response ex vivo in the future.

bioengineering↗

DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies

Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms of repeat mapping and variant phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs and insertions and deletions (indels) from both short-read and long-read data, with modes for whole-genome and exome sequencing, and able to run on tumor-normal, tumor-only, and with FFPE-prepared samples. To help address the dearth of publicly available training and benchmarking data for somatic variant detection, we generated and make openly available a dataset of five matched tumor-normal cell line pairs sequenced with Illumina, PacBio HiFi, and Oxford Nanopore Technologies, along with benchmark variant sets. Across samples and technologies (short-read and long-read), DeepSomatic consistently outperforms existing callers, particularly for indels.

bioinformatics↗

MICOS Complex Loss Governs Age-Associated Murine Mitochondrial Architecture and Metabolism in the Liver, While Sam50 Dictates Diet Changes

Background & AimsAging is associated with a significant decline in mitochondrial function in the liver, leading to an increased risk of liver disease. This study examines age-related changes in the mitochondrial structure of human and murine livers using a combination of Serial Block-Face Scanning Electron Microscopy (SBF-SEM) and mass spectrometry approaches. MethodsThis study integrates mitochondrial structure analysis in a murine model with an analysis of liver architecture, lipogenesis, and genetically regulated gene expression in human cohorts. We explored the Mitochondrial Contact Site and Cristae Organizing System (MICOS) complex using SBF-SEM, three-dimensional reconstruction with Amira software, and mass spectrometry techniques. ResultsAging leads to a reduction in mitochondrial size and complexity, resulting in changes in the metabolomic and lipidomic profiles of murine liver cells that are comparable to those observed in aged human samples. We find that genetically modeled expression of MICOS complex genes OPA1 and CHCHD3 is associated with chronic liver disease phenotypes within a large biobank population. Furthermore, we observed dysregulated mitochondrial calcium handling and increased oxidative stress due to the disruption of the MICOS complex. ConclusionOur study highlights the age-associated decline in mitochondrial complexity and metabolic regulation within the aging murine liver and the human population. We have identified that these changes are partially attributable to the age-related loss of the MICOS complex. Impact and implicationsThis study offers new insights into the changes to mitochondrial ultrastructure that occur during aging. Using SBF-SEM, the quantification of young and aged murine mitochondrial structure was performed, which had previously been an underexplored avenue for measuring mitochondrial changes. The discovery of mitochondrial ultrastructural changes, in conjunction with measurements of age-associated metabolic alterations and gene association data, provides a model for how changes in MICOS expression may modulate age-related impairment of hepatic mitochondria. These results provide a new model by which changes in MICOS protein expression may both cause and be a potential therapeutic target for age-related impairment in hepatic function. HighlightsDecreased modeled expression of CHCHD3 in individuals of European genetic ancestry is linked to liver transplant and cirrhosis, while decreased modeled expression of OPA1 in individuals of African genetic ancestry is associated with chronic liver disease and cirrhosis. Aging alters liver lipid accumulation, MICOS mRNA levels, and disease markers. Aging reduces the volume and complexity of murine liver ultrastructure. Aging and diet significantly alter the MICOS complex in mice. Knockdown of Mic60 and Chchd6 lowers Ca2+ uptake, retention, and induces oxidative stress in HepG2 cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/599846v3_ufig1.gif" ALT="Figure 1000"> View larger version (47K): org.highwire.dtl.DTLVardef@1cdd61corg.highwire.dtl.DTLVardef@a3fb74org.highwire.dtl.DTLVardef@1d1ad36org.highwire.dtl.DTLVardef@c2e55f_HPS_FORMAT_FIGEXP M_FIG C_FIG Liver aging causes metabolic, lipidomic, and mitochondrial structural alterations, reflecting age-dependent losses in the MICOS complex. Key components of the MICOS complex (MIC60, CHCHD3 and CHCHD6) are illustrated.

physiology↗

Myeloid Cell Glucocorticoid, Not Mineralocorticoid Receptor Signaling, Contributes to Salt-Sensitive Hypertension in Humans via Cortisol

BACKGROUNDSalt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular morbidity and mortality, yet the etiology is poorly understood. We previously found that serum/glucocorticoid-regulated kinase 1 (SGK1) and epoxyeicosatrienoic acids (EETs) regulate epithelial sodium channel (ENaC)-dependent sodium entry into monocyte-derived antigen-presenting cells (APCs) and activation of NADPH oxidase, leading to the formation of isolevuglandins (IsoLGs) in SSBP. Whereas aldosterone via the mineralocorticoid receptor (MR) activates SGK1 leading to hypertension, our past findings indicate that levels of plasma aldosterone do not correlate with SSBP, and there is little to no MR expression in APCs. Thus, we hypothesized that cortisol acting via the glucocorticoid receptor (GR), not the MR in APCs mediates SGK1 actions to induce SSBP. METHODSWe performed cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq) analysis on peripheral blood mononuclear cells of humans rigorously phenotyped for SSBP using an inpatient salt loading/depletion protocol to determine expression of MR, GR, and SGK1 in immune cells. In additional experiments, we performed bulk transcriptomic analysis on isolated human monocytes following in vitro treatment with high salt from a separate cohort. We then measured urine and plasma cortisol, cortisone, renin, and aldosterone. Subsequently, we measured the association of these hormones with changes in systolic, diastolic, mean arterial pressure and pulse pressure as well as immune cell activation via IsoLG formation. RESULTSWe found that myeloid APCs predominantly express the GR and SGK1 with no expression of the MR. Expression of the GR in APCs increased after salt loading and decreased with salt depletion in salt-sensitive but not salt-resistant people and was associated with increased expression of SGK1. Moreover, we found that plasma and urine cortisol/cortisone but not aldosterone/renin correlated with SSBP and APCs activation via IsoLGs. We also found that cortisol negatively correlates with EETs. CONCLUSIONOur findings suggest that renal cortisol signaling via the GR but not the MR in APCs contributes to SSBP via cortisol. Urine and plasma cortisol may provide an important currently unavailable feasible diagnostic tool for SSBP. Moreover, cortisol-GR-SGK1-ENaC signaling pathway may provide treatment options for SSBP. Novelty and RelevanceO_ST_ABSWhat Is New?C_ST_ABSO_LIAlthough salt sensitivity is a major risk factor for cardiovascular morbidity and mortality, the mechanisms underlying the salt sensitivity of blood pressure (SSBP) are poorly understood. C_LIO_LIHigh salt modifies glucocorticoid-receptor expression in antigen-presenting cells (APCs), suggesting a critical role of glucocorticoids in SSBP. C_LIO_LIElevated glucocorticoid receptor (GR) expression compared to mineralocorticoid receptor (MR) expression in APCs provides evidence for a GR-dependent pathway to SSBP. Isolevuglandins (IsoLGs) increased in APCs in vitro after hydrocortisone treatment compared to aldosterone treatment, indicating that cortisol was the predominant driver of IsoLG production in these cells. C_LIO_LIOur studies suggest a mechanism for SGK1 expression through GR activation by cortisol that differs from the currently accepted mechanism for SSBP pathogenesis. C_LI What Is Relevant?O_LIAlthough aldosterone has been used to study SSBP, there has been no consideration of cortisol as a major driver of the condition. C_LIO_LIUnderstanding alternative inflammatory pathways that affect SSBP may provide insights into the mechanism of SSBP and suggest a range of therapeutic targets. C_LIO_LIOur studies may provide a practical approach to understanding and treating salt-sensitive hypertension. C_LI Clinical/Pathophysiological Implications?O_LIOur findings firmly support a GR-dependent signaling pathway for activating SSBP via SGK1 expression. A cortisol-driven mechanism could provide a practical approach for targeted treatments for salt-sensitive hypertension. Moreover, it could pave the way for a diagnostic approach. C_LI

physiology↗

GenMPI: Cluster Scalable Variant Calling forShort/Long Reads Sequencing Data

Rapid technological advancements in sequencing technologies allow producing cost effective and high volume sequencing data. Processing this data for real-time clinical diagnosis is potentially time-consuming if done on a single computing node. This work presents a complete variant calling workflow, implemented using the Message Passing Interface (MPI) to leverage the benefits of high bandwidth interconnects. This solution (GenMPI) is portable and flexible, meaning it can be deployed to any private or public cluster/cloud infrastructure. Any alignment or variant calling application can be used with minimal adaptation. To achieve high performance, compressed input data can be streamed in parallel to alignment applications while uncompressed data can use internal file seek functionality to eliminate the bottleneck of streaming input data from a single node. Alignment output can be directly stored in multiple chromosome-specific SAM files or a single SAM file. After alignment, a distributed queue using MPI RMA (Remote Memory Access) atomic operations is created for sorting, indexing, marking of duplicates (if necessary) and variant calling applications. We ensure the accuracy of variants as compared to the original single node methods. We also show that for 300x coverage data, alignment scales almost linearly up to 64 nodes (8192 CPU cores). Overall, this work outperforms existing big data based workflows by a factor of two and is almost 20% faster than other MPI-based implementations for alignment without any extra memory overheads. Sorting, indexing, duplicate removal and variant calling is also scalable up to 8 nodes cluster. For pair-end short-reads (Illumina) data, we integrated the BWA-MEM aligner and three variant callers (GATK HaplotypeCaller, DeepVariant and Octopus), while for long-reads data, we integrated the Minimap2 aligner and three different variant callers (DeepVariant, DeepVariant with WhatsHap for phasing (PacBio) and Clair3 (ONT)). All codes and scripts are available at: https://github.com/abs-tudelft/gen-mpi

bioinformatics↗

Communication-Efficient Cluster Scalable Genomics Data Processing Using Apache Arrow Flight

Current cluster scaled genomics data processing solutions rely on big data frameworks like Apache Spark, Hadoop and HDFS for data scheduling, processing and storage. These frameworks come with additional computation and memory overheads by default. It has been observed that scaling genomics dataset processing beyond 32 nodes is not efficient on such frameworks. To overcome the inefficiencies of big data frameworks for processing genomics data on clusters, we introduce a low-overhead and highly scalable solution on a SLURM based HPC batch system. This solution uses Apache Arrow as in-memory columnar data format to store genomics data efficiently and Arrow Flight as a network protocol to move and schedule this data across the HPC nodes with low communication overhead. As a use case, we use NGS short reads DNA sequencing data for pre-processing and variant calling applications. This solution outperforms existing Apache Spark based big data solutions in term of both computation time (2x) and lower communication overhead (more than 20-60% depending on cluster size). Our solution has similar performance to MPI-based HPC solutions, with the added advantage of easy programmability and transparent big data scalability. The whole solution is Python and shell script based, which makes it flexible to update and integrate alternative variant callers. Our solution is publicly available on GitHub at https://github.com/abs-tudelft/time-to-fly-high/genomics.

bioinformatics↗

Obesity impairs therapeutic efficacy of mesenchymal stem cells by inhibiting cardiolipin-dependent mitophagy and intercellular mitochondrial transfer in mouse models of airway allergic inflammation

Mesenchymal stem cell (MSC) transplantation alleviates metabolic defects in diseased recipient cells by intercellular mitochondrial transport (IMT). However, the effect of host metabolic conditions on MSCs in general, and IMT in particular, has largely remained unexplored. This study has identified a molecular pathway that primarily governs the metabolic function and IMT of MSCs. We found underlying mitochondrial dysfunction, impaired mitophagy, and reduced IMT in MSCs derived from high-fat diet (HFD)-induced obese mice (MSC-Ob). Mechanistically, MSC-Ob failed to sequester their damaged mitochondria into LC3-dependent autophagosomes due to decrease in mitochondrial cardiolipin content, which we propose as a putative mitophagy receptor for LC3 in MSCs. Functionally, MSC-Ob exhibited diminished potential to rescue metabolic deficits and cell death in stress-induced epithelial cells. In a small molecule screen, we found pyrroloquinoline quinone (PQQ) as a regulator of mitophagy and IMT. Long-term culture of MSC-Ob with PQQ (MSC-ObPQQ) restored cardiolipin content and sequestration of mitochondria to autophagosomes with concomitant activation of mitophagy. Upon co-culture, MSC-ObPQQ rescued cell death in stress-induced epithelial cells by enhancing IMT. The beneficial effect of PQQ was also evident in MSCs derived from human subjects in an in vitro model. In two independent mice models, the transplantation of MSC-ObPQQ restored IMT to airway epithelial cells, improved their mitochondrial metabolism and attenuated features of allergic airway inflammation (AAI). However, unmodulated MSC-Ob failed to do so. In summary, we uncover the molecular mechanism leading to the therapeutic decline of obese-derived MSCs and highlight the importance of pharmacological modulation of these cells for therapeutic intervention.

cell biology↗

Comprehensive studies of Head Maralla, Punjab, Pakistan vegetation for ethnopharmacological and ethnobotanical uses and their elaboration through quantitative indices

Head Maralla is a non-recognized wetland with diversified flora that becomes focus of current studies. Whole plant or their parts are being used for treating various maladies and they are the integral part of livelihood in the area. Unique species including Osmunda regalis is used for blood and renal diseases purifier. Wild plant resources are key to traditional ethnobotanical knowledge based practices and industrial applications. Current study reports Head Marala inhabitants interaction with these resources and identify priorities at species and habitat level for conservation. Four sites viz., River Tavi, Upstream Chenab, River Manawarwala Tavi and Bhalolpur were designated to record traditional knowledge through questionnaire and interviews during field trips. One hundred nineteen (119) plant species were identified belonging to 54 families, of which 87 species were of dicot, 12monocots, 05ferns, and 4 species of bryophytes. Fifty percent of the plant species were utilized as a whole for therapeutic purposes, followed by leaves which had more than 20% usage of total consumption. Ailments viz., urination (14%) followed by cough (8%), cold (7%), stomach (6%), asthma (6%), constipation (5%), laxative (5%), diarrhea (4%) etc., were associated with vegetation. Bronchial disorders, pneumonia, dyspepsia, anthelmintic and kidney stones, etc., were also among other diseases commonly cured by traditional knowledge. Fifteen percent of vegetation contributes as fodder species consumed by local community for livestock while almost 17% of local plants were utilized for industrial purposes like timber, fuel, furniture, wooden pots and sports goods. In conclusion the ecosystem of Head Maralla is a complex of aquatic, terrestrial and agricultural land that is located on climatic and geographical divides, which further add to botanical interest as included many wetland habitats with unique diversity of plants. It is suggested to devise comprehensive conservation strategies to safe indigenous knowledge in systematic way for comprehending ecological services.

plant biology↗

ArrowSAM: In-Memory Genomics Data Processing through Apache Arrow Framework

The rapidly growing size of genomics data bases, driven by advances in sequencing technologies, demands fast and cost-effective processing. However, processing this data creates many challenges, particularly in selecting appropriate algorithms and computing platforms. Computing systems need data closer to the processor for fast processing. Traditionally, due to cost, volatility and other physical constraints of DRAM, it was not feasible to place large amounts of working data sets in memory. However, new emerging storage class memories allow storing and processing big data closer to the processor. In this work, we show how the commonly used genomics data format, Sequence Alignment/Map (SAM), can be presented in the Apache Arrow in-memory data representation to benefit of in-memory processing and to ensure better scalability through shared memory objects, by avoiding large (de)-serialization overheads in cross-language interoperability. To demonstrate the benefits of such a system, we propose ArrowSAM, an in-memory SAM format that uses the Apache Arrow framework, and integrate it into genome pre-processing pipelines including BWA-MEM, Picard and Sambamba. Results show 15x and 2.4x speedups as compared to Picard and Sambamba, respectively. The code and scripts for running all workflows are freely available at https://github.com/abs-tudelft/ArrowSAM.

genomics↗

Massive parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity

As a prototype of genomics-guided precision medicine, individualized thiopurine dosing based on pharmacogenetics is a highly effective way to mitigate hematopoietic toxicity of this class of drugs. Recently, NUDT15 deficiency was identified as a novel genetic cause of thiopurine toxicity, and NUDT15-informed preemptive dose reduction is quickly adopted in clinical settings. To exhaustively identify pharmacogenetic variants in this gene, we developed massively parallel NUDT15 function assays to determine variants effect on protein abundance and thiopurine cytotoxicity. Of the 3,097 possible missense variants, we characterized the abundance of 2,922 variants and found 54 hotspot residues at which variants resulted in complete loss of protein stability. Analyzing 2,935 variants in the thiopurine cytotoxicity-based assay, we identified 17 additional residues where variants altered NUDT15 activity without affecting protein stability. We identified structural elements key to NUDT15 stability and/or catalytical activity with single amino-acid resolution. Functional effects for NUDT15 variants accurately predicted toxicity risk alleles in 2,398 patients treated with thiopurines, with 100% sensitivity and specificity, in contrast with poor performance of bioinformatic prediction algorithms. In conclusion, our massively parallel variant function assays identified 1,103 deleterious NUDT15 variants, providing a comprehensive reference of variant function and vastly improving the ability to implement pharmacogenetics-guided thiopurine treatment individualization.

genomics↗

A blood-based prognostic biomarker in inflammatory bowel disease

ObjectiveWe have previously described a prognostic transcriptional signature in CD8 T cells that separates inflammatory bowel disease (IBD) patients into 2 phenotypically-distinct subgroups, which we termed IBD1 and IBD2. Here we sought to develop a blood-based prognostic test that could identify these patient subgroups without the need for cell separation, and thus be suitable for routine clinical use in Crohns disease (CD) and ulcerative colitis (UC). DesignPatients with active IBD were recruited before treatment. Transcriptomic analyses were performed on purified CD8 T cells and/or whole blood. Detailed phenotype information was collected prospectively. IBD1/IBD2 patient subgroups were identified by consensus clustering of CD8 T cell transcriptomes. In a training cohort, statistical (machine) learning was used to identify groups of genes ("classifiers") whose differential expression in whole blood re-created the IBD1/IBD2 patient subgroups. Genes from the best classifiers were qPCR-optimised, and further statistical learning was applied to the qPCR dataset to identify the optimal classifier, which was locked-down for further testing. Independent validation was sought in separate cohorts of CD (n=66) and UC patients (n=57). ResultsIn both independent validation cohorts, a 17-gene qPCR-based classifier stratified patients into two distinct subgroups. Irrespective of the underlying diagnosis, IBDhi patients (analogous to the poor prognosis IBD1 subgroup) experienced significantly more aggressive disease than IBDlo patients (analogous to IBD2), with earlier need for treatment escalation and more escalations over time. ConclusionThis is the first validated prognostic biomarker that can predict prognosis in newly-diagnosed IBD patients, and represents a step towards personalised therapy. What is already known about this subject?The course of CD and UC varies considerably between patients, but reliable prognostic markers are not available in clinical practice. This hinders disease management because treatment approaches that would be optimal for patients with indolent disease - characterised by infrequent flare-ups that can be readily controlled by first-line therapy - will inevitably undertreat those with progressive disease. Conversely, strategies that would appropriately control frequently-relapsing, progressive disease will expose patients with more quiescent disease to the risks and side effects of unnecessary treatment. We have previously described a CD8 T cell gene expression signature that corresponds to differences in T cell exhaustion, is detectable during active untreated disease (including at diagnosis), and predicts disease course in both UC and CD. However, the need for cell separation and microarray-based gene expression analysis would make this difficult to translate to clinical practice. What are the new findings?We have developed, optimised, and independently validated a whole blood qPCR-based classifier - designed to identify the IBD1 and IBD2 patient subgroups - that can reliably predict prognosis in patients with CD or UC from diagnosis without the need for cell separation. We also present a detailed phenotypic update on the disease course experienced by patients in either the IBD1/IBDhi or IBD2/IBDlo subgroups, incorporating both expanded patient cohorts and substantially longer follow-up. This affords new insights into the spectrum of therapies that are differentially required in these patient subgroups, and reinforces their association with disease prognosis. How might it impact on clinical practice in the foreseeable future?The qPCR-based classifier has performance characteristics that compare favourably to prognostic biomarkers currently in use in oncology, and should be sufficient to guide therapy from diagnosis in patients with CD or UC. This represents an important step towards personalised therapy in inflammatory bowel disease.

genomics↗

HLA-DQA1*05 is associated with the development of antibodies to anti-TNF therapy

BackgroundAnti-tumour necrosis factor (anti-TNF) therapies are the most widely used biologic therapies for treating immune-mediated diseases. Their efficacy is significantly reduced by the development of anti-drug antibodies which can lead to treatment failure and adverse reactions. The biological mechanisms underlying antibody development are unknown but the ability to identify subjects at higher risk would have significant clinical benefits.\n\nMethodsThe PANTS cohort consists of Crohns disease patients recruited prior to first administration of anti-TNF, with serial measurements of anti-drug antibody titres. We performed a genome-wide association study across 1240 individuals from this cohort to identify genetic variants associated with anti-drug antibody development.\n\nFindingsThe Human Leukocyte Antigen allele, HLA-DQA1*05, carried by approximately 40% of Europeans, significantly increased the rate of anti-drug antibody development (hazard ratio [HR], 1.90; 95% confidence interval [CI], 1.60 to 2.25; P=5.88x10-13). This association was consistent for patients treated with adalimumab (HR, 1.89; 95% CI, 1.32 to 2.70) and infliximab (HR, 1.92; 95% CI, 1.57 to 2.33), and for patients treated with mono-(HR, 1.75; 95% CI, 1.37 to 2.22) or combination therapy with immunomodulators (HR, 2.0; 95% CI, 1.57 to 2.58).\n\nInterpretationHLA-DQA1*05 is significantly associated with an increased rate of anti-drug antibody formation in patients with Crohns disease treated with infliximab and adalimumab. Pre-treatment HLA-DQA1*05 genetic testing may help personalise the choice of anti-TNF therapy and allow the targeted use of immunomodulator therapy to minimise risk and maximise response.

genomics↗