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Ahmadi, M.

Publications and source records attributed to Ahmadi, M..

15 recordsLinked to original sources

Temporal-to-spatial patterning of embryonic structures can involve active transformation of temporal information rather than direct mapping

How spatial patterns arise during embryonic development is classically explained by the French Flag model, in which cells acquire positional identities by interpreting morphogen concentration thresholds. However, in many developmental systems, spatial patterns instead emerge progressively through temporal programs of gene expression that are transformed into spatial organization. For example, in the short-germ insect Tribolium castaneum, both periodic pair-rule gene expressions that generate body segments and non-periodic gap gene expressions that establish regional identities arise sequentially at the posterior and propagate anteriorly in waves across the developing embryo. Understanding how such temporal gene expression programs are translated into spatial patterns remains a major challenge. To address this problem, we developed a sequential multiplexed imaging strategy based on hybridization chain reaction (HCR), enabling visualization of up to ten anterior-posterior (AP) patterning genes within the same Tribolium embryo. By combining this approach with intronic-exonic labeling, we established a framework to infer gene expression dynamics and propagatory behavior during AP patterning. Using this framework, we show that gap gene expression domains remain dynamic and continue to propagate during tissue elongation, indicating that spatial patterns are actively remodeled throughout development. We then directly compared temporal gene activation at the posterior with the resulting spatial organization of pair-rule and gap genes. Surprisingly, while primary pair-rule genes preserve their temporal phase relationships in space, gap genes do not. Instead, the relative positioning of gap gene domains progressively changes as they move anteriorly, indicating that the final spatial organization of gap genes is actively reshaped during propagation rather than being directly inherited from the initial temporal sequence. The continued propagatory behavior of gap gene domains suggests that such reshaping could arise through differential propagation dynamics between genes and/or through progressive reconfiguration of underlying gene regulatory interactions during pattern formation. Together, these findings reveal that temporal-to-spatial patterning can involve active transformation of temporal information rather than a simple mapping from time into space.

developmental biology↗

On the state of protein function prediction: a report on the fourth CAFA challenge

BackgroundThe Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4). ResultsCAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.

bioinformatics↗

Development of a Fully Non-Viral 1XX-enhanced BCMA CAR-T Cell Therapy for Multiple Myeloma

Multiple myeloma (MM) is a clonal plasma cell malignancy characterized by bone marrow infiltration, monoclonal immunoglobulin production, and microenvironmental dysregulation that leads to systemic organ damage. The advent of B-cell maturation antigen (BCMA)-directed chimeric antigen receptor (CAR) T-cell therapy has induced unprecedented responses and durability for patients with relapsed/refractory MM. These outcomes are rarely observed with prior salvage strategies, although relapse remains the predominant long-term challenge for most patients. The two currently approved BCMA CAR-T cell products use viral vectors to semi-randomly insert the CAR gene, which results in heterogeneous genomic composition and variability in efficacy, safety, and product consistency. To address these challenges, we integrated targeted CRISPR genome engineering with precise CAR transgene insertion at the T-cell receptor alpha constant (TRAC) locus, 1XX CAR signaling architecture to enhance potency and durability, and non-viral manufacturing with a single-stranded DNA repair template to improve efficiency and yield. This approach confers physiological CAR expression, reduces insertional mutagenesis, and improves persistence by mitigating tonic signaling and exhaustion. Our GMP manufacturing process consistently achieved high CAR integration (37.7-72.7%) and yields across all full-scale runs and met predefined release criteria for identity, purity, safety, and quality. In NSG mouse models of MM, the UCCT-BCMA-1 product exhibited exceptionally potent tumor control, CAR-T cell expansion 100-1000-fold greater than that of lentiviral constructs, and durable clearance of myeloma cells after multiple rechallenges. These findings establish a CRISPR-edited, fully non-viral manufacturing platform for next-generation 1XX-BCMA CAR-T therapies with enhanced persistence, safety, and efficacy. One Sentence SummaryCRISPR-engineered, TRAC-targeted 1XX-BCMA CAR-T therapy with improved safety, potency, and persistence in relapsed and refractory multiple myeloma.

cancer biology↗

Bioimaging Data Management Workflow for Plasma Medicine

Bioimaging experiments in plasma medicine generate complex datasets that go beyond conventional imaging studies by combining microscopy data with heterogeneous metadata from biological experiments and highly parameterized gas plasma treatments. Plasma exposure conditions, such as device configuration, gas composition, and treatment conditions, are critical determinants of biological outcome, yet they are rarely captured in a standardized, machine-readable, and reusable manner. To address this gap, we present a research data management (RDM) workflow that operationalizes the Findable, Accessible, Interoperable, and Reusable (FAIR) principles across the bioimaging data lifecycle in plasma medicine. The workflow is implemented as a structured pipeline integrating open-source tools, including OMERO for image data management, eLabFTW as an electronic laboratory notebook, Adamant for schema-driven metadata collection, and Micro-Meta App for standardized documentation of microscopy acquisition settings that are connected via programming interfaces to enable persistent linkage of metadata to image datasets using standardized annotations. The workflow is documented in a reproducible tutorial with an open-source Python Jupyter notebook hosted on GitHub. By integrating plasma treatment metadata with imaging data, this approach improves reproducibility, cross-study comparability, and data reuse in plasma medicine research.

bioinformatics↗

Gene network switching provides a mechanistic basis for time-to-space translation in insect embryonic patterning

The French Flag model has long served as the prevailing framework for explaining how morphogen gradients generate spatial domains during embryonic development. More recently, however, evidence has shown that many tissues instead establish patterns by translating the sequential activation of genes (organized into genetic cascades) into spatial domains. This translation is thought to occur through modulation of the speed or timing of cascade progression, but the mechanisms underlying such temporal control remain unclear. Two models have been proposed: the general kinetic modulation model, in which morphogens influence global kinetic factors such as transcription and decay rates, and the gene regulatory network (GRN) switching model, in which morphogens reconfigure regulatory interactions so that genes initially function within a genetic cascade driving sequential activation, but are later integrated into a stabilizing network that locks their expression into mutually reinforcing domains. This transition is hypothesized to occur through a shift from a dynamic GRN (a genetic cascade that drives sequential activations) to a static GRN (a stabilizing network that maintains gene expression domains). Using gap genes in Tribolium castaneum as a model, we combined HCR in situ hybridization, parental RNA interference, and computational modeling to test these hypotheses. We show that gap genes initially act in a genetic cascade producing sequential activations, followed by a morphogen-dependent reconfiguration that stabilizes spatial domains. In particular, we identify the Mlpt-Svb complex as a key stabilizing factor that maintains svb expression anteriorly after its initial activation in the posterior. Computational simulations reproduce experimental phenotypes and support GRN switching as the underlying mechanism. Together, these findings demonstrate how morphogen-driven rewiring of network interactions converts temporal cascades into stable spatial patterns, providing a mechanistic basis for robust anterior- posterior patterning in insect embryos and beyond.

developmental biology↗

TUMOR-INFILTRATING NOCICEPTOR NEURONS PROMOTE IMMUNOSUPPRESSION

Nociceptor neurons impact tumor immunity. Removing nociceptor neurons reduced myeloid-derived suppressor cell (MDSCs) tumor infiltration in mouse models of head and neck carcinoma and melanoma. Carcinoma-released small extracellular vesicles (sEVs) attract nociceptive nerves to tumors. sEV-deficient tumors fail to develop in mice lacking nociceptor neurons. Exposure of dorsal root ganglia (DRG) neurons to cancer sEVs elevated expression of Substance P, IL-6 and injury-related neuronal markers while treatment with cancer sEVs and cytotoxic CD8 T-cells induced an immunosuppressive state (increased exhaustion ligands and cytokines). Cancer patient sEVs enhanced DRG responses to capsaicin, indicating increased nociceptor sensitivity. Conditioned media from DRG and cancer cell co-cultures promoted expression of MDSC markers in primary bone marrow cells while DRG conditioned media together with cancer sEVs induced checkpoint expression on T-cells. Our findings indicate that nociceptor neurons facilitate CD8+ T cell exhaustion and enhance MDSC infiltration. Targeting nociceptor-released IL-6 emerges as a novel strategy to disrupt harmful neuro-immune interactions in cancer and enhance anti-tumor immunity.

cancer biology↗

Accelerating CAR T cell manufacturing with an automated next-day process

The traditional method of CAR T cell production involves lengthy ex vivo culture times which can result in the reduction of crucial naive T cell subsets. Moreover, traditional CAR T cell therapy manufacturing processes can prolong time-to-patient and contribute to disease progression. In this study, we describe an innovative and automated 24-hour CAR T manufacturing process that yields a higher percentage of naive/stem-cell like T cells which have increased cytotoxic activity and cytokine release. The data supports the feasibility of implementing this streamlined manufacturing process in clinics. This approach also has the potential to enhance CAR T therapy efficacy and improve patient access to therapy.

bioengineering↗

PRMT5 is required for full-length HTT expression by repressing multiple proximal intronic polyadenylation sites

Expansion of the CAG trinucleotide repeat tract in exon 1 of the Huntingtin (HTT) gene above a threshold of [~]36 repeats causes Huntingtons disease (HD) through the expression of a polyglutamine-expanded form of the HTT protein. This mutation triggers wide-ranging cellular and biochemical pathologies leading to cognitive, motor, and psychiatric symptoms in HD patients. As accurate splicing is required to produce the full-length HTT protein of [~]348 kDa, targeting HTT splicing with small molecule drugs is a compelling approach to lower HTT protein levels to treat HD, and splice modulators are being tested in the clinic. Here, we identify PRMT5 as a novel regulator of HTT mRNA splicing and alternative polyadenylation. PRMT5 inhibition disrupts the splicing of HTT introns 9 and 10, leading to activation of multiple proximal intronic polyadenylation sites within these introns and promoting premature termination, cleavage and polyadenylation (PCPA) of the HTT mRNA, thus lowering total HTT protein levels. We also detected increasing levels of these truncated, intron-containing HTT transcripts across a series of neuronal differentiation samples which correlated with lower PRMT5 expression. Notably, PRMT5 inhibition in glioblastoma (GBM) stem cells potently induced neuronal differentiation. We posit that PRMT5-mediated regulation of intronic polyadenylation, premature termination and cleavage of the HTT mRNA modulates HTT expression and plays an important role during embryonic development and neuronal differentiation.

neuroscience↗

Crowdsourcing Temporal Transcriptomic Coronavirus Host Infection Data: resources, guide, and novel insights.

The emergence of SARS-CoV-2 reawakened the need to rapidly understand the molecular etiologies, pandemic potential, and prospective treatments of infectious agents. The lack of existing data on SARS-CoV-2 hampered early attempts to treat severe forms of COVID-19 during the pandemic. This study coupled existing transcriptomic data from SARS-CoV-1 lung infection animal studies with crowdsourcing statistical approaches to derive temporal meta-signatures of host responses during early viral accumulation and subsequent clearance stages. Unsupervised and supervised machine learning approaches identified top dysregulated genes and potential biomarkers (e.g., CXCL10, BEX2, and ADM). Temporal meta-signatures revealed distinct gene expression programs with biological implications to a series of host responses underlying sustained Cxcl10 expression and Stat signaling. Cell cycle switched from G1/G0 phase genes, early in infection, to a G2/M gene signature during late infection that correlated with the enrichment of DNA Damage Response and Repair genes. The SARS-CoV-1 meta-signatures were shown to closely emulate human SARS-CoV-2 host responses from emerging RNAseq, single cell and proteomics data with early monocyte-macrophage activation followed by lymphocyte proliferation. The circulatory hormone adrenomedullin was observed as maximally elevated in elderly patients that died from COVID-19. Stage-specific correlations to compounds with potential to treat COVID-19 and future coronavirus infections were in part validated by a subset of twenty-four that are in clinical trials to treat COVID-19. This study represents a roadmap to leverage existing data in the public domain to derive novel molecular and biological insights and potential treatments to emerging human pathogens. The data from this study is available in an interactive portal (http://18.222.95.219:8047).

bioinformatics↗

A Comparison of Weighted Stochastic Simulation Methods

1Rare events are of particular interest in biology because rare biochemical events may be catastrophic to a biological system. To estimate the probability of rare events, several weighted stochastic simulation methods have been developed. Unfortunately, the robustness of these methods is questionable. Here, an analysis of weighted stochastic simulation methods is presented. The methods considered here fail to accomplish the task of rare event simulation, in general, suggesting that new methods are necessary to adequately study rare biological events.

systems biology↗

The Mediator tail module cooperates with proneural factors to determine fate identity in Glioblastoma.

Glioblastoma stem cells (GSCs) exhibit latent neuronal lineage differentiation potential governed by the proneural transcription factor Achaete-scute homolog 1 (ASCL1) and harnessing and promoting terminal neuronal differentiation has been proposed as a novel therapeutic strategy. Here, using a genome-wide CRISPR suppressor screen we identified genes required for ASCL1-mediated neuronal differentiation. This approach revealed a specialized function of the Mediator complex tail module and of its subunits MED24 and MED25 for this process in GSCs, human fetal neural stem cells and pluripotent stem cells. We show that upon induction of neuronal differentiation MED25 is recruited to genomic loci co-occupied by ASCL1 to regulate neurogenic gene expression programs. MED24 and MED25 are sufficient to induce neuronal differentiation in GSC cultures and to mediate neuronal differentiation in multiple contexts. Collectively our data expand our understanding of the mechanisms underlying directed terminal neuronal differentiation in brain tumor stem cells and point to a unique function of the Mediator tail in neuronal reprogramming.

cell biology↗

Hydrazines as versatile chemical biology probes and drug-discovery tools for cofactor-dependent enzymes

Known chemoproteomic probes generally use warheads that tag a single type of amino acid or modified form thereof to identify cases in which its hyper-reactivity underpins function. Much important biochemistry derives from electron-poor enzyme cofactors, transient intermediates and chemically-labile regulatory modifications, but probes for such species are underdeveloped. Here, we have innovated a versatile class of chemoproteomic probes for this less charted hemisphere of the proteome by using hydrazine as the common chemical warhead. Its electron-rich nature allows it to react by both polar and radicaloid mechanisms and to target multiple, pharmacologically important functional classes of enzymes bearing diverse organic and inorganic cofactors. Probe attachment can be blocked by active-site-directed inhibitors, and elaboration of the warhead supports connection of a target to a lead compound. The capacity of substituted hydrazines to profile, discover and inhibit diverse cofactor-dependent enzymes enables cell and tissue imaging and makes this platform useful for enzyme and drug discovery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/154864v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1e1a54forg.highwire.dtl.DTLVardef@12be680org.highwire.dtl.DTLVardef@129e027org.highwire.dtl.DTLVardef@3b2317_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Colon Cancer and SARS-CoV-2: Impact of ACE2 Expression in Susceptibility to COVID-19

Novel coronavirus disease (COVID-19) pandemic has become a global health emergency. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with angiotensin-converting enzyme 2 (ACE2) to enter the cells and infects diverse human tissues. It has been reported that a few conditions, including cancer, predispose individuals to SARS-CoV-2 infection and severe form of COVID-19. These findings led us to evaluate the susceptibility of colon adenocarcinoma (COAD) patients to SARS-CoV-2 infection by investigation of ACE2 expression in their tumor tissues. The expression analysis revealed that both mRNA and protein levels of ACE2 had increased in colon cancer samples than normal group. Next, the prognosis analysis has indicated that the upregulation of ACE2 was not correlated with patient survival outcomes. Further assessment displayed the hypomethylation of the ACE2 gene promoter in COAD patients. Surprisingly, this methylation status has a strong negative correlation with ACE2 gene expression. The functional enrichment analysis of the genes that had similar expression patterns with ACE2 in colon cancer tissues demonstrated that they mainly enriched in Vitamin digestion and absorption, Sulfur relay system, and Fat digestion and absorption pathways. Finally, we found that ACE2 gene expression had a significant association with the immune cell infiltration levels in COAD patients. In conclusion, it has plausible that COAD patients are more likely to be infected with SARS-CoV-2 and experience severe injuries. Moreover, COVID-19 would bring unfavorable survival outcomes of patients with colon cancer by the way of immune cell infiltration linked process. The present study highlights the importance of preventive actions for COAD patients during the COVID-19 pandemic.

genetics↗

The functional genomic circuitry of human glioblastoma stem cells

SummarySuccessful glioblastoma (GBM) therapies have remained elusive due to limitations in understanding mechanisms of growth and survival of the tumorigenic population. Using CRISPR-Cas9 approaches in patient-derived GBM stem cells to interrogate function of the coding genome, we identify diverse actionable pathways responsible for growth that reveal the gene-essential circuitry of GBM stemness. In particular, we describe the Sox developmental transcription factor family; H3K79 methylation by DOT1L; and ufmylation stress responsiveness programs as essential for GBM stemness. Additionally, we find mechanisms of temozolomide resistance and sensitivity that could lead to combination strategies with this standard of care treatment. By reaching beyond static genome analysis of bulk tumors, with a genome wide functional approach, we dive deep into a broad range of biological processes to provide new understanding of GBM growth and treatment resistance.\n\nSignificanceGlioblastoma (GBM) remains an incurable disease despite an increasingly thorough depth of knowledge of the genomic and epigenomic alterations of bulk tumors. Evidence from multiple approaches support that GBM reflects an aberrant developmental hierarchy, with GBM stem cells (GSCs), fueling tumor growth and invasion. The properties of this tumor subpopulation may also in part explain treatment resistance and disease recurrence. Unfortunately, we still have a limited knowledge of the molecular circuitry of these cells and progress has been slow as we have not been able, until recently, to interrogate function at the genome-wide scale. Here, using parallel genome-wide CRISPR-Cas9 screens, we identify the essential genes for GSC growth. Further, by screening in the presence of low and high dose temozolomide, we identify mechanisms of drug resistance and sensitivity. These functional screens in patient derived cells reveal new aspects of GBM biology and identify a diversity of actionable targets such as genes governing stem cell traits, epigenome regulation and the response to stress stimuli.

cancer biology↗