Biology subjects

Siddiqui, A.

Publications and source records attributed to Siddiqui, A..

14 recordsLinked to original sources

bioRxiv2024

Deep Profiling of Plasma Proteoforms with Engineered Nanoparticles for Top-down Proteomics

The dynamic range challenge for detection of proteins and their proteoforms in human plasma has been well documented. Here, we use the nanoparticle protein corona approach to enrich low-abundant proteins selectively and reproducibly from human plasma and use top-down proteomics to quantify differential enrichment for the 2841 detected proteoforms from 114 proteins. Furthermore, nanoparticle enrichment allowed top-down detection of proteoforms between [~]1 {micro}g/mL and [~]10 pg/mL in absolute abundance, providing up to 105-fold increase in proteome depth over neat plasma in which only proteoforms from abundant proteins (>1 {micro}g/mL) were detected. The ability to monitor medium and some low abundant proteoforms through reproducible enrichment significantly extends the applicability of proteoform research by adding depth beyond albumin, immunoglobins and apolipoproteins to uncover many involved in immunity and cell signaling. As proteoforms carry unique information content relative to peptides, this report opens the door to deeper proteoform sequencing in clinical proteomics of disease or aging cohorts.

biochemistry↗

bioRxiv2024

Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics

Alzheimers disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimers Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The ProteographTM Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.

neuroscience↗

bioRxiv2023

The germline regulates longevity and somatic repair in a sex-specific manner

Classical evolutionary theories propose tradeoffs between reproduction, damage repair, and lifespan. However, the specific role of the germline in shaping vertebrate aging remains largely unknown. Here, we use the turquoise killifish (N. furzeri) to genetically arrest germline development at discrete stages, and examine how different modes of infertility impact life-history. We first construct a comprehensive single-cell gonadal atlas, providing cell-type-specific markers for downstream phenotypic analysis. Next, we show that germline depletion - but not arresting germline differentiation - enhances damage repair in female killifish. Conversely, germline-depleted males instead showed an extension in lifespan and rejuvenated metabolic functions. Through further transcriptomic analysis, we highlight enrichment of pro-longevity pathways and genes in germline-depleted male killifish and demonstrate functional conservation of how these factors may regulate longevity in germline-depleted C. elegans. Our results therefore demonstrate that different germline manipulation paradigms can yield pronounced sexually dimorphic phenotypes, implying alternative responses to classical evolutionary tradeoffs.

genetics↗

bioRxiv2023

The N6-methyladenosine demethylase ALKBH5 regulates the hypoxic HBV transcriptome.

Chronic hepatitis B is a global health problem and current treatments only suppress hepatitis B virus (HBV) infection, highlighting the need for new curative treatments. Oxygen levels influence HBV replication and we previously reported that hypoxia inducible factors (HIFs) activate the basal core promoter to transcribe pre-genomic RNA. Application of a probe-enriched long-read sequencing method to map the HBV transcriptome showed an increased abundance of all viral RNAs under low oxygen or hypoxic conditions. Importantly, the hypoxic-associated increase in HBV transcripts was dependent on N6-methyladenosine (m6A) modifications and an m6A DRACH motif in the 5 stem loop of pre-genomic RNA defined transcript half-life under hypoxic conditions. Given the essential role of m6A modifications in the viral transcriptome we assessed the oxygen-dependent expression of RNA demethylases and bio-informatic analysis of published single cell RNA-seq of murine liver showed an increased expression of the RNA demethylase ALKBH5 in the peri-central low oxygen region. In vitro studies with a human hepatocyte derived HepG2 cell line showed increased ALKBH5 gene expression under hypoxic conditions. Silencing the demethylase reduced the levels of HBV pre-genomic RNA and host gene (CA9, NDRG1, VEGFA, BNIP3, FUT11, GAP and P4HA1) transcripts and this was mediated via reduced HIF expression. In summary, our study highlights a previously unrecognized role for ALKBH5 in orchestrating viral and cellular transcriptional responses to low oxygen. Author SummaryOxygen levels influence HBV replication and hypoxia inducible factors (HIFs) activate HBV transcription. Long-read sequencing and mapping the HBV transcriptome showed an increased abundance of all viral RNAs under hypoxic conditions that was dependent on N6-methyladenosine modifications. Investigating the oxygen-dependent expression of RNA demethylases identified ALKBH5 as a hypoxic activated gene and silencing its expression showed a key role in regulating HBV and host gene expression under hypoxic conditions.

molecular biology↗

bioRxiv2023

Protein Coronas on Functionalized Nanoparticles Enable Quantitative and Precise Large-Scale Deep Plasma Proteomics

BackgroundThe wide dynamic range of circulating proteins coupled with the diversity of proteoforms present in plasma has historically impeded comprehensive and quantitative characterization of the plasma proteome at scale. Automated nanoparticle (NP) protein corona-based proteomics workflows can efficiently compress the dynamic range of protein abundances into a mass spectrometry (MS)-accessible detection range. This enhances the depth and scalability of quantitative MS-based methods, which can elucidate the molecular mechanisms of biological processes, discover new protein biomarkers, and improve comprehensiveness of MS-based diagnostics. MethodsInvestigating multi-species spike-in experiments and a cohort, we investigated fold-change accuracy, linearity, precision, and statistical power for the using the Proteograph Product Suite, a deep plasma proteomics workflow, in conjunction with multiple MS instruments. ResultsWe show that NP-based workflows enable accurate identification (false discovery rate of 1%) of more than 6,000 proteins from plasma (Orbitrap Astral) and, compared to a gold standard neat plasma workflow that is limited to the detection of hundreds of plasma proteins, facilitate quantification of more proteins with accurate fold-changes, high linearity, and precision. Furthermore, we demonstrate high statistical power for the discovery of biomarkers in small- and large-scale cohorts. ConclusionsThe automated NP workflow enables high-throughput, deep, and quantitative plasma proteomics investigation with sufficient power to discover new biomarker signatures with a peptide level resolution.

biochemistry↗

bioRxiv2023

Nanoparticle Enrichment Mass-Spectrometry Proteomics Identifies Protein Altering Variants for Precise pQTL Mapping

Genome-wide association studies (GWAS) with proteomics generate hypotheses on protein function and offer genetic evidence for drug target prioritization. Although most protein quantitative loci (pQTLs) have so far been identified by high-throughput affinity proteomics platforms, these methods also have some limitations, such as uncertainty about target identity, non-specific binding of aptamers, and inability to handle epitope-modifying variants that affect affinity binding. Mass spectrometry (MS) proteomics has the potential to overcome these challenges and broaden the scope of pQTL studies. Here, we employ the recently developed MS-based Proteograph workflow (Seer, Inc.) to quantify over 18,000 unique peptides from almost 3,000 proteins in more than 320 blood samples from a multi-ethnic cohort. We implement a bottom-up MS-proteomics approach for the detection and quantification of blood-circulating proteins in the presence of protein altering variants (PAVs). We identify 184 PAVs located in 137 genes that are significantly associated with their corresponding variant peptides in MS data (MS-PAVs). Half of these MS-PAVs (94) overlap with cis-pQTLs previously identified by affinity proteomics pQTL studies, thus confirming the target specificity of the affinity binders. An additional 54 MS-PAVs overlap with trans-pQTLs (and not cis-pQTLs) in affinity proteomics studies, thus identifying the putatively causal cis-encoded protein and providing experimental evidence for its presence in blood. The remaining 36 MS-PAVs have not been previously reported and include proteins that may be inaccessible to affinity proteomics, such as a variant in the incretin pro-peptide (GIP) that associates with type 2 diabetes and cardiovascular disease. Overall, our study introduces a novel approach for analyzing MS-based proteomics data within the GWAS context, provides new insights relevant to genetics-based drug discovery, and highlights the potential of MS-proteomics technologies when applied at population scale. HighlightsO_LIThis is the first pQTL study that uses the Proteograph (Seer Inc.) mass spectrometry-based proteomics workflow. C_LIO_LIWe introduce a novel bottom-up proteomics approach that accounts for protein altering variants in the detection of pQTLs. C_LIO_LIWe confirm the target and potential epitope effects of affinity binders for cis-pQTLs from affinity proteomics studies. C_LIO_LIWe establish putatively causal proteins for known affinity proteomics trans-pQTLs and confirm their presence in blood. C_LIO_LIWe identify novel protein altering variants in proteins of clinical relevance that may not be accessible to affinity proteomics. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/537640v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@5db14forg.highwire.dtl.DTLVardef@123c1edorg.highwire.dtl.DTLVardef@90ebb6org.highwire.dtl.DTLVardef@6320ff_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

A Clinically Useful and Biologically Informative Genomic Classifier for Papillary Thyroid Cancer

Clinical management of papillary thyroid cancer depends on estimations of prognosis. Standard care, which relies on prognostication based on clinicopathologic features, is inaccurate. We applied a machine learning algorithm (HighLifeR) to 502 cases annotated by The Cancer Genome Atlas Project to derive an accurate molecular prognostic classifier. Unsupervised analysis of the 82 genes that were most closely associated with recurrence after surgery enabled identification of three unique molecular subtypes. One subtype had a high recurrence rate, an immunosuppressed microenvironment, and enrichment of the EZH2-HOTAIR pathway. Two other unique molecular subtypes with a lower rate of recurrence were identified, including one subtype with a paucity of BRAFV600E mutations and a high rate of RAS mutations. The genomic risk classifier, in addition to tumor size and lymph node status, enabled effective prognostication that outperformed the American Thyroid Association clinical risk stratification. The genomic classifier we derived can potentially be applied preoperatively to direct clinical decision-making. Distinct biological features of molecular subtypes also have implications regarding sensitivity to radioactive iodine, EZH2 inhibitors, and immune checkpoint inhibitors.

cancer biology↗

bioRxiv2022

Widespread, depth-dependent microstructural damage in the cortex of children with drug resistant focal epilepsy: A quantitative T1 and T2 mapping study

ObjectiveTissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes, treatment-related side-effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilised quantitative MRI, which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. MethodsTo assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy [age-range=4-18 years] and 46 typically-developing children [age-range=2-18 years]. We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically-defined abnormalities (MRI-positive) and healthy controls, and tested if this could classify patients without reported radiological abnormalities (MRI-negative). ResultsWe uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 62% at 100% specificity on held-out MRI-negative patients. SignificanceThese findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically-identified abnormalities, and potentially evident pre-symptomatically. Key PointsO_LIWe assessed cortical microstructure in children with focal epilepsy C_LIO_LIQuantitative T1 and T2 relaxometry (qT1 and qT2) was measured in the neocortex C_LIO_LIPatients showed extensive qT1/qT2 increases and intracortical organization changes C_LIO_LIAlterations may appear during cerebral development, prior to disease onset C_LI

neuroscience↗

bioRxiv2022

Enhanced competitive protein exchange at the nano-bio interface enables ultra-deep coverage of the human plasma proteome

We have developed a scalable system that leverages protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Introducing proprietary engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. Here we demonstrate the importance of tuning the protein to NP-surface ratio (P/NP), which determines the competition between proteins for binding. We demonstrate how optimized P/NP ratio affects protein corona composition, ultimately enhancing performance of a fully automated NP-based deep proteomic workflow (Proteograph). By limiting the available binding surface of NPs and increasing the binding competition, we identify 1.2 - 1.7x more proteins with only 1% false discovery rate on the surface of each NP, and up to 3x compared to a standard neat plasma proteomics workflow. Moreover, increased competition means proteins are more consistently identified and quantified across replicates, yielding precise quantification and improved coverage of the plasma proteome when using multiple physicochemically distinct NPs. In summary, by optimizing NPs and assay conditions, we capture a larger and more diverse set of proteins, enabling deep proteomic studies at scale.

biophysics↗

bioRxiv2022

Peptide-centric analyses of human plasma enable increased resolution of biological insights into non-small cell lung cancer relative to protein-centric analysis

Advancements in deep plasma proteomics are enabling high-resolution measurement of plasma proteoforms, which may reveal a rich source of novel biomarkers previously concealed by aggregated protein methods. Here, we analyze 188 plasma proteomes from non-small cell lung cancer subjects (NSCLC) and controls to identify NSCLC-associated protein isoforms by examining differentially abundant peptides as a proxy for isoform-specific exon usage. We find four proteins comprised of peptides with opposite patterns of abundance between cancer and control subjects. One of these proteins, BMP1, has known isoforms that can explain this differential pattern, for which the abundance of the NSCLC-associated isoform increases with stage of NSCLC progression. The presence of cancer and control-associated isoforms suggests differential regulation of BMP1 isoforms. The identified BMP1 isoforms have known functional differences, which may reveal insights into mechanisms impacting NSCLC disease progression.

cancer biology↗

bioRxiv2020

Spatial heterogeneity in resources alters selective dynamics in Drosophila melanogaster

Environmental features can alter the behaviours and phenotypes of organisms and populations evolving within them including the dynamics between natural and sexual selection. Experimental environmental manipulation, particularly when conducted in experiments where the dynamics of the purging of deleterious alleles are compared, has demonstrated both direct and indirect effects on the strength and direction of selection. However, many of these experiments are conducted with fairly simplistic environments when it is not always clear how or why particular forms of spatial heterogeneity may influence behaviour or selection. Using Drosophila melanogaster, we tested three different spatial environments designed to determine if spatial constraint of critical resources influences the efficiency of natural and sexual selection. We conducted two allele purging experiments to 1) assess the effects of these spatial treatments on the selective dynamics of six recessive mutations, and 2) determine how these dynamics changed when sexual selection was relaxed and the spatial area was reduced. We found that allele purging dynamics depended on spatial environment, however the patterns of purging rates between the environments differed across distinct deleterious mutations. We also found that for two of the mutations, the addition of sexual selection increased the purging rate.

evolutionary biology↗

bioRxiv2020

A Second Generation Leishmanization Vaccine with a Markerless Attenuated Leishmania major Strain using CRISPR gene editing

Leishmaniasis is a debilitating and often fatal neglected tropical disease caused by Leishmania protozoa transmitted by infected sand flies. Vaccination through leishmanization with live Leishmania major has been used successfully but is no longer practiced because it resulted in unacceptable skin lesions. A second generation leishmanization is described here using a CRISPR genome edited L. major strain (LmCen-/-). Notably, LmCen-/- is the first genetically engineered gene deleted Leishmania strain that is antibiotic resistant marker free and does not have any off-target mutations. Mice immunized with LmCen-/- had virtually no visible lesions following challenge with L. major-infected sand flies while non-immunized animals developed large and progressive lesions with a 2-log fold higher parasite burden. LmCen-/- immunization showed protection and an immune response comparable to leishmanization. LmCen-/- is safe since it was unable to cause disease even in immunocompromised mice, induces robust host protection against vector sand fly challenge and because it is marker free, can be advanced to human vaccine trials.

microbiology↗

bioRxiv2019

Single Cell RNA-seq reveals ectopic and aberrant lung resident cell populations in Idiopathic Pulmonary Fibrosis

We provide a single cell atlas of Idiopathic Pulmonary Fibrosis (IPF), a fatal interstitial lung disease, focusing on resident lung cell populations. By profiling 312,928 cells from 32 IPF, 29 healthy control and 18 chronic obstructive pulmonary disease (COPD) lungs, we demonstrate that IPF is characterized by changes in discrete subpopulations of cells in the three major parenchymal compartments: the epithelium, endothelium and stroma. Among epithelial cells, we identify a novel population of IPF enriched aberrant basaloid cells that co-express basal epithelial markers, mesenchymal markers, senescence markers, developmental transcription factors and are located at the edge of myofibroblast foci in the IPF lung. Among vascular endothelial cells in the in IPF lung parenchyma we identify an expanded cell population transcriptomically identical to vascular endothelial cells normally restricted to the bronchial circulation. We confirm the presence of both populations by immunohistochemistry and independent datasets. Among stromal cells we identify fibroblasts and myofibroblasts in both control and IPF lungs and leverage manifold-based algorithms diffusion maps and diffusion pseudotime to infer the origins of the activated IPF myofibroblast. Our work provides a comprehensive catalogue of the aberrant cellular transcriptional programs in IPF, demonstrates a new framework for analyzing complex disease with scRNAseq, and provides the largest lung disease single-cell atlas to date.

genomics↗

bioRxiv2018

Thymidylate synthase maintains the de-differentiated state of aggressive breast cancers

Cancer cells frequently boost nucleotide metabolism (NM) to support their increased proliferation, but the consequences of elevated NM on tumor de-differentiation are mostly unexplored. Here, we identified a role for thymidylate synthase (TS), a NM enzyme and established drug target, in cancer cell de-differentiation and investigated its clinical significance in breast cancer (BC). In vitro, TS knockdown increased the population of CD24+ differentiated cells, and attenuated migration and sphere-formation. RNA-seq profiling indicated a repression of epithelial-to-mesenchymal transition (EMT) signature genes upon TS knockdown, and TS-deficient cells showed an increased ability to invade and metastasize in vivo, consistent with the occurrence of a partial EMT phenotype. Mechanistically, TS enzymatic activity was found essential for the maintenance of the EMT/stem-like state by fueling a DPYD-dependent pyrimidine catabolism. In patient tissues, TS levels were found significantly higher in poorly differentiated and in triple negative BC (TNBC), and strongly correlated with worse prognosis. The present study provides the rationale to study in-depth the role of NM at the crossroads of proliferation and differentiation, and depicts new avenues for the design of novel drug combinations for the treatment of BC.

cancer biology↗