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Gandhi, M.

Publications and source records attributed to Gandhi, M..

8 recordsLinked to original sources

MassID provides near complete annotation of metabolomics data with identification probabilities

Liquid chromatography coupled to mass spectrometry (LC/MS) is a powerful tool in metabolomics research, generating tens-of-thousands of signals from a single biological sample. However, current software solutions for unbiased assessment of metabolomics data analysis are limited by complex sources of noise and non-quantitative metabolite identifications that make results difficult to interpret. Here, we present MassID, a cloud-based untargeted metabolomics pipeline that aims to overcome the innate challenges of unbiased metabolite analysis and perform end-to-end data processing, transforming raw spectra to normalized and identified metabolite profiles. MassID incorporates a suite of software functionalities, including deep learning-based peak detection and comprehensive noise filtering. In addition, with MassID we introduce a novel software module: DecoID2 that enables probabilistic metabolite identification for false discovery rate (FDR)-controlled metabolomics. When applied to a human plasma dataset, MassID results in near-complete signal annotation, identification of >4,000 metabolites (including >1,200 compounds at an FDR <5%) across four complementary LC/MS runs, and enables integrated downstream analyses to understand biochemical dysregulation at both the molecular and pathway level. When compared to the Metabolomics Standards Initiative (MSI) confidence levels, identification probability generally correlated with MSI levels. However, only 356/418 of MSI Level 1 compounds were identified with <5% FDR and the remaining 884 FDR < 5% compounds were identified from MSI L2-L3 compounds, highlighting the enhanced specificity and discovery potential achieved by MassID.

bioinformatics↗

Break-induced replication underlies formation of inverted triplications and generates unexpected diversity in haplotype structures

BackgroundThe duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a type of complex genomic rearrangement (CGR) hypothesized to result from replicative repair of DNA due to replication fork collapse. It is often mediated by a pair of inverted low-copy repeats (LCR) followed by iterative template switches resulting in at least two breakpoint junctions in cis. Although it has been identified as an important mutation signature of pathogenicity for genomic disorders and cancer genomes, its architecture remains unresolved and is predicted to display at least four structural variation (SV) haplotypes. ResultsHere we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the genomic DNA of 24 patients with neurodevelopmental disorders identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted SV haplotypes. Using a combination of short-read genome sequencing (GS), long- read GS, optical genome mapping and StrandSeq the haplotype structure was resolved in 18 samples. This approach refined the point of template switching between inverted LCRs in 4 samples revealing a DNA segment of [~]2.2-5.5 kb of 100% nucleotide similarity. A prediction model was developed to infer the LCR used to mediate the non-allelic homology repair. ConclusionsThese data provide experimental evidence supporting the hypothesis that inverted LCRs act as a recombinant substrate in replication-based repair mechanisms. Such inverted repeats are particularly relevant for formation of copy-number associated inversions, including the DUP-TRP/INV-DUP structures. Moreover, this type of CGR can result in multiple conformers which contributes to generate diverse SV haplotypes in susceptible loci.

genetics↗

Mass Spectrometry Imaging of Hair Identifies Daily Maraviroc Adherence in HPTN 069/ACTG A5305

Objective measures of adherence for antiretrovirals used as pre-exposure prophylaxis (PrEP) are critical for improving preventative efficacy in both clinical trials and real-world application. Current objective adherence measures either reflect only recent behavior (eg days for plasma or urine) or cumulative behavior (eg months for dried blood spots). We measured the accumulation of the antiretroviral drug maraviroc (MVC) in hair strands by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging (MSI) to evaluate adherence behavior longitudinally at high temporal resolution. An MSI threshold for classifying daily adherence was established using clinical samples from healthy volunteers following directly observed dosing of 1 to 7 doses MVC/week. We then used the benchmarked MSI assay to classify adherence to MVC-based PrEP regimens in hair samples collected throughout the 49-week HPTN069/ACTGA5305 study. We found that only ~32% of investigated hair samples collected during the studys active dosing period showed consistent daily PrEP adherence throughout a retrospective period of 30 days, and also found that profiles of daily individual adherence from MSI hair analysis could identify when patients were and were not taking study drug. The assessment of adherence from MSI hair strand analysis was 62% lower than adherence classified using paired plasma samples, the latter of which may be influenced by white-coat adherence. These findings demonstrate the ability of MSI hair analysis to examine daily variability of adherence behavior over a longer-term measurement and offer the potential for longitudinal comparison with risk behavior to target patient-specific adherence interventions and improve outcomes.

pharmacology and toxicology↗

Inhibitory interneurons within the deep dorsal horn integrate convergent sensory input to regulate motor performance

To achieve smooth motor performance in a changing sensory environment, motor outputs must be constantly updated in response to sensory feedback. Inhibitory interneurons in the spinal cord play an essential role in shaping motor activity by gating the transmission of sensory information and setting the pattern and rhythm of motor neurons. Here, we identify the medial deep dorsal horn of the spinal cord as a "hot zone" of convergent proprioceptive and cutaneous information from the hindlimb, where inhibitory neurons show increased responsiveness to sensory input and are preferentially recruited during locomotion in comparison to excitatory neurons. We identify a novel population of glycinergic inhibitory neurons within the deep dorsal horn that express parvalbumin (dPV) and receive convergent proprioceptive and cutaneous input from the paw. We show that dPVs possess intrinsic properties that support spontaneous discharge, even in the absence of synaptic input. However, a drug cocktail mimicking descending input (5-HT, dopamine, NMDA) amplifies dPV output, while cutaneous and proprioceptive inputs shape the temporal dynamics of dPV activity. These findings suggest dPV-mediated inhibition is modulated by behavioral state and can be fine-tuned by sensory input. Using intersectional genetic strategies, we selectively target spinal cord dPVs and demonstrate their capacity to provide divergent ipsilateral inhibition to both pre-motor and motor networks of the ventral horn, thereby controlling the timing and magnitude of cutaneous-evoked muscle activity. Manipulating the activity of dPVs during treadmill locomotion results in altered limb kinematics at the transition of stance to swing and altered step cycle timing at increased speeds. To investigate the effects of manipulating dPV activity on broader sets of motor behaviors, we used depth vision and machine learning to quantify and scale naturalistic behavior. We find that although sub-movements remain stable, the transitions between sub-movements are reduced, suggesting a role in movement switching. In sum, our study reveals a new model by which sensory convergence and inhibitory divergence produce a surprisingly flexible influence on motor networks to increase the diversity of mechanisms by which sensory input facilitates smooth movement and context-appropriate transitions. HighlightsO_LIInhibitory deep dorsal horn interneurons integrate convergent proprioceptive and cutaneous sensory inputs from the paw and are preferentially recruited during locomotion. C_LIO_LIDeep dorsal horn parvalbumin+ interneurons (dPVs) represent a population of glycinergic interneurons that can provide sustained inhibitory control. C_LIO_LISensory input engages dPVs to facilitate inhibition with high temporal precision and reduced variability. C_LIO_LIdPVs contribute to the ipsilateral inhibitory control of motor and premotor networks of the ventral horn, thereby gating the magnitude and timing of cutaneous-evoked flexor and extensor muscle activity. C_LIO_LIIn vivo, dPVs modulate gait dynamics in a state- and phase-dependent manner, to ensure smooth movement transitions between step-cycle phases and naturalistic sub-movements. C_LI

neuroscience↗

Comprehensive Structural Variant Detection: From Mosaic to Population-Level

Long-read Structural Variation (SV) calling remains a challenging but highly accurate way to identify complex genomic alterations. Here, we present Sniffles2, which is faster and more accurate than state-of-the-art SV caller across different coverages, sequencing technologies, and SV types. Furthermore, Sniffles2 solves the problem of family- to population-level SV calling to produce fully genotyped VCF files by introducing a gVCF file concept. Across 11 probands, we accurately identified causative SVs around MECP2, including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we successfully identified multiple mosaic SVs across a multiple system atrophy patient brain. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements. In summary, we demonstrate the utility and versatility of Sniffles2 to identify SVs from the mosaic to population levels.

bioinformatics↗

Nephrotoxicity of the BRAF-kinase inhibitor Vemurafenib isdriven by off-target Ferrochelatase inhibition

A multitude of disease and therapy related factors drive the frequent development of renal disorders in cancer patients. Along with chemotherapy, the newer targeted therapeutics can also cause renal dysfunction through on and off-target mechanisms. Interestingly, among the small-molecule inhibitors approved for the treatment of cancers that harbor BRAF-kinase activating mutations, vemurafenib can trigger tubular damage and acute kidney injury (AKI). To investigate the underlying mechanisms, here, we have developed cell culture and mouse models of vemurafenib nephrotoxicity. Our studies show that at clinically relevant concentrations vemurafenib induces cell-death in transformed and primary murine and human renal tubular epithelial cells (RTEC). In mice, two weeks of daily vemurafenib treatment causes moderate AKI with histopathological characteristics of RTEC injury. Importantly, RTEC-specific BRAF gene deletion did not influence renal function under normal conditions or alter the severity of vemurafenib-associated renal impairment. Instead, we found that inhibition of ferrochelatase (FECH), an enzyme involved in heme biosynthesis contributes to vemurafenib nephrotoxicity. FECH overexpression protected RTECs and conversely FECH knockdown increased the sensitivity to vemurafenib nephrotoxicity. Collectively, these studies suggest that vemurafenib-associated RTEC dysfunction and nephrotoxicity is BRAF-independent and caused in part by off-target FECH inhibition. Translational StatementBRAF is the most frequently mutated protein kinase and a critical oncogenic driver in human cancers. In melanoma and other cancers with BRAF activating mutations, BRAF targeted small-molecule therapeutics such as vemurafenib, and dabrafenib have shown remarkable clinical benefits. However, recent clinical studies have shown that a significant number of patients that receive vemurafenib develop AKI through mechanisms that remain unknown. The present study describes the development of novel experimental models of vemurafenib nephrotoxicity and reveals the underlying off-target mechanisms that contribute to renal injury.

pharmacology and toxicology↗

SOX9 promotes stress-responsive transcription of VGF nerve growth factor inducible gene in kidney epithelial cells

Acute kidney injury (AKI) is a common clinical condition associated with diverse etiologies and abrupt loss of renal function. In patients with sepsis, rhabdomyolysis, cancer, as well as cardiovascular disorders, the underlying disease or associated therapeutic interventions can cause hypoxic, cytotoxic, and inflammatory insults to renal tubular epithelial cells (RTECs) resulting in the onset of AKI. To uncover stress-responsive disease-modifying genes, here we have carried out renal transcriptome profiling in three distinct murine models of AKI. We find that Vgf nerve growth factor inducible gene upregulation is a common transcriptional stress response in RTECs to ischemia, cisplatin, and rhabdomyolysis-associated renal injury. The Vgf gene encodes a secretory peptide precursor protein that has critical neuro-endocrine functions; however, its role in the kidneys remains unknown. Our functional studies show that RTEC-specific Vgf gene ablation exacerbates ischemia, cisplatin, and rhabdomyolysis-associated AKI in vivo and cisplatin-induced RTEC cell death in vitro. Importantly, addback experiments showed that aggravation of cisplatin-induced renal injury caused by Vgf gene ablation is partly reversed by TLQP-21, a Vgf-derived peptide. Finally, in vitro and in vivo mechanistic studies showed that injury-induced Vgf upregulation in RTECs is driven by the transcriptional regulator Sox9. These findings reveal a crucial downstream target of the Sox9-directed transcriptional program and identify Vgf as a stress-responsive protective gene in kidney epithelial cells.AbbreviationsAKIAcute kidney injuryRTECrenal tubular epithelial cellsBUNblood urea nitrogenChIPchromatin immunoprecipitationSox9SRY-Box transcription factor 9.View Full Text

cell biology↗

Pathognomonic and epistatic genetic alterations in B-cell non-Hodgkin lymphoma

B-cell non-Hodgkins lymphoma (B-NHL) encompasses multiple clinically and phenotypically distinct subtypes of malignancy with unique molecular etiologies. Common subtypes of B-NHL such as diffuse large B-cell lymphoma (DLBCL) have been comprehensively interrogated at the genomic level. But rarer subtypes such as mantle cell lymphoma (MCL) remain sparsely characterized. Furthermore, multiple B-NHL subtypes have thus far not been comprehensively compared using the same methodology to identify conserved or subtype-specific patterns of genomic alterations. Here, we employed a large targeted hybrid-capture sequencing approach encompassing 380 genes to interrogate the genomic landscapes of 685 B-NHL tumors at high depth; including DLBCL, MCL, follicular lymphoma (FL), and Burkitt lymphoma (BL). We identified conserved hallmarks of B-NHL that were deregulated in the majority of tumor from each subtype, including the frequent genetic deregulation of the ubiquitin proteasome system (UPS). In addition, we identified subtype-specific patterns of genetic alterations, including clusters of co-occurring mutations and DNA copy number alterations. The cumulative burden of mutations within a single cluster were more discriminatory of B-NHL subtypes than individual mutations, implicating likely patterns of genetic cooperation that contribute to disease etiology. We therefore provide the first cross-sectional analysis of mutations and DNA copy number alterations across major B-NHL subtypes and a framework of co-occurring genetic alterations that deregulate genetic hallmarks and likely cooperate in lymphomagenesis.

genomics↗