Biology subjects

Raja, R.

Publications and source records attributed to Raja, R..

11 recordsLinked to original sources

bioRxiv2026

Human neurons stimulated with IFNγ present HLA class I-restricted autoantigens to cytotoxic CD8+ T cells

Interferon-{gamma} (IFN{gamma}) signaling is prominent in inflammatory CNS microenvironments across many neurological disorders, but the neuronal peptides presented on HLA class I under these conditions and their functional consequences for CD8+ T cells remain incompletely defined. Here we combine human iPSC-derived human neural aggregates (HNAs), HLA class I immunoprecipitation coupled to LC-MS/MS immunopeptidomics, and microfluidic co-culture assays to map IFN{gamma}-induced neuronal antigen presentation and test antigen-specific cytotoxicity. IFN{gamma} stimulation induced robust HLA class I expression in HNAs and enabled recovery of a canonical 8-12-mer class I ligandome enriched for 9-mers. Neuron-restricted expression of a synapsin-driven polyepitope cassette yielded presentation of defined neoantigen 9-mer peptides on donor HLA class I molecules and, in the presence of IFN{gamma}, elicited activation of autologous antigen-specific CD8+ T cells and consequent antigen-dependent neurite injury. Across four donors, comparative immunopeptidomics identified large IFN{gamma}-unique neural peptide repertoires distinct from matched fibroblasts and revealed a consistent enrichment of predicted high-affinity binders on HLA-B allotypes. Finally, {beta}2-microglobulin deletion ablated peptide recovery, and neuron-restricted {beta}2-microglobulin reconstitution enabled identification of neuron-derived peptides, including peptides derived from neurofilament light (NEFL) that were shared across donors and presented on multiple HLA allotypes. Together, these data provide an integrated platform for neuronal autoantigen discovery and functional validation and support a model in which IFN{gamma}-driven neuronal HLA class I presentation creates an HLA-B-weighted epitope landscape that can be recognized by autoreactive cytotoxic CD8+ T cells.

immunology↗

bioRxiv2025

Comparing Orientation-Dependent Transverse Relaxation at 3T and 7T: Deciphering Anisotropic Relaxation Mechanisms in White Matter

Purpose: This work aims to elucidate the mechanisms underlying orientation-dependent transverse relaxation in human brain white matter (WM), which have long been ambiguous. Methods: We analyzed publicly available 3T and 7T DTI datasets (b-values = 1000 and 2000 s/mm2) from 25 young adults participating in the Human Connectome Project. Orientation-dependent transverse relaxation R2 profiles from whole brain WM were generated from T2-weighted images (b-value = 0) and characterized using a previously developed cone model based on the generalized magic angle effect (MAE). Derived anisotropic R2 or R2a values were compared between different magnetic fields. Similar comparisons were also conducted for the derived R2a values from whole brain WM and two fiber tracts, based on gradient-echo signals reported in the literature. Classical relaxation theories predict that the ratio of (R2a (7T))/R2a (3T)) will be unity or (7/3)^2 (i.e., approximately 5.4) if the measured orientation-dependent R2 arises exclusively from MAE or from the previously proposed susceptibility effect, respectively. Results: Fitted model parameters were comparable for DTI datasets with b-values of 1000 and 2000 (s/mm2). The fitted R2a increased, on average, from 3.6{+/-}1.1 (1/s) at 3T to 5.4{+/-}1.5 (1/s) at 7T for DTI datasets with a b-value=1000 s/mm2. The measured ratio of (R2a (7T))/(R2a (3T)) was thus approximately 1.5. However, based on gradient-echo signals, this ratio essentially became unity within the measurement precision. Conclusion: This study suggests that MAE is the primary mechanism for the observed orientation-dependent transverse relaxation at 3T in human brain WM, offering a different perspective from previous literature.

biophysics↗

bioRxiv2025

Unifying Orientation-Dependent Relaxation and Diffusion Around Axonal Fibers from DTI: Characterizing Fiber-Tract-Specific Anisotropic R2 Profiles of the Corpus Callosum

This work aims to characterize fiber-tract-specific orientation-dependent R2 from the seven callosal segments (CC1-CC7) based on human brain Connectome high-resolution DTI datasets. WM voxels from each segment were masked by the thresholds of FA and mode of anisotropy. Encoded in T2W images (b-value = 0), an orientation-dependent R2 profile was constructed based on voxel-wise fiber orientations and characterized by a "cone" model. This allowed [Formula], an orientation-dependent or anisotropic R2, to be separated from its orientation-independent or isotropic counterpart. Except for [Formula], no discernible differences were found for the fits between the two b-values. On average, [Formula] increased from 2.4{+/-}0.2 (1/s) to 3.2{+/-}0.3 (1/s) as the b-value increased. Furthermore, [Formula] showed an increasing trend from CC1 to CC7 and the open angle of the cone fluctuated around 65{degrees}. As usual, FA was found increasing from CC1 to CC7 and from a higher to a lower b-value. In conclusion, we have shown that fiber-tract-specific Anisotropic R2 profiles from the callosal segments can be characterized by a cone model. The proposed method offers a unique opportunity to reevaluate existing clinical DTI studies and optimize new ones for characterizing specific WM tracts in both healthy and diseased subjects.

biophysics↗

bioRxiv2024

Interferon-Induced PARP14-Mediated ADP-Ribosylation in p62 Bodies Requires an Active Ubiquitin-Proteasome System

Biomolecular condensates are cellular compartments without enveloping membranes, enabling them to dynamically adjust their composition in response to environmental changes through post-translational modifications. A recent study has revealed that interferon-induced ADP-ribosylation (ADPr), which can be reversed by a SARS-CoV-2-encoded hydrolase, is enriched within a condensate. However, the identity of the condensate and responsible host ADP-ribosyltransferase remain elusive. Here, we demonstrate that interferon induces ADPr through transcriptional activation of PARP14, requiring both its physical presence and catalytic activity for condensate formation. Interferon-induced ADPr colocalizes with PARP14, and these PARP14/ADPr condensates contain key components of p62 bodies--including the selective autophagy receptor p62 and its binding partner NBR1, along with K48-linked and K63-linked polyubiquitin chains--but lack the autophagosome marker LC3B. Knockdown of p62 disrupts the formation of these ADPr condensates. Importantly, these structures are unaffected by autophagy inhibition but depend on both ubiquitin activation and proteasome activity. Taken together, these findings demonstrate that interferon triggers PARP14-mediated ADP-ribosylation in p62 bodies, which requires an active ubiquitin-proteasome system.

cell biology↗

bioRxiv2023

Decentralized Mixed Effects Modeling in COINSTAC

Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging due to its large dimensionality and inherent multi-level covariance structure. In addition, as large-scale collaborative projects become commonplace in neuroimaging, data must increasingly be stored and analysed at different locations. In such settings, substantial overheads occur in terms of data transfer and coordination between participating research groups. In some cases, data cannot be pooled together due to privacy or regulatory concerns. In this work, we propose a decentralized LME model to perform a large-scale analysis of data from different collaborations without sharing or pooling. This method is efficient as it overcomes the hurdles of data privacy for sharing and has lower bandwidth and memory requirements for analysis than the centralized modeling approach. We evaluate our model using features extracted from structural magnetic resonance imaging (sMRI) data. Results highlight gray matter reductions in the temporal lobe/insula and medical front regions demonstrate the correctness of decentralized LME models. Our analysis also demonstrates that decentralized LME models achieve similar performance compared to the models trained with all the data in one location. We also implement the decentralized LME approach in COINSTAC, a decentralized platform for federating neuroimaging analysis, to demonstrate its value to the neuroimaging community.

neuroscience↗

bioRxiv2023

Modeling transcriptional regulation of the cell cycle using a novel cybernetic-inspired approach

Quantitative understanding of cellular processes, such as cell cycle and differentiation, is impeded by various forms of complexity ranging from myriad molecular players and their multilevel regulatory interactions, cellular evolution with multiple intermediate stages, lack of elucidation of cause-effect relationships among the many system players, and the computational complexity associated with the profusion of variables and parameters. In this paper, we present an elegant modeling framework based on the cybernetic concept that biological regulation is inspired by objectives embedding entirely novel strategies for dimension reduction, process stage specification through the system dynamics, and innovative causal association of regulatory events with the ability to predict the evolution of the dynamical system. The elementary step of the modeling strategy involves stage-specific objective functions that are computationally-determined from experiments, augmented with dynamical network computations involving end point objective functions, mutual information, change point detection, and maximal clique centrality. We demonstrate the power of the method through application to the mammalian cell cycle, which involves thousands of biomolecules engaged in signaling, transcription, and regulation. Starting with a fine-grained transcriptional description obtained from RNA sequencing measurements, we develop an initial model, which is then dynamically modeled using the cybernetic-inspired method (CIM), utilizing the strategies described above. The CIM is able to distill the most significant interactions from a multitude of possibilities. In addition to capturing the complexity of regulatory processes in a mechanistically causal and stage-specific manner, we identify the functional network modules, including novel cell cycle stages. Our model is able to predict future cell cycles consistent with experimental measurements. We posit that this state-of-the-art framework has the promise to extend to the dynamics of other biological processes, with a potential to provide novel mechanistic insights. STATEMENT OF SIGNIFICANCECellular processes like cell cycle are overly complex, involving multiple players interacting at multiple levels, and explicit modeling of such systems is challenging. The availability of longitudinal RNA measurements provides an opportunity to "reverse-engineer" for novel regulatory models. We develop a novel framework, inspired using goal-oriented cybernetic model, to implicitly model transcriptional regulation by constraining the system using inferred temporal goals. A preliminary causal network based on information-theory is used as a starting point, and our framework is used to distill the network to temporally-based networks containing essential molecular players. The strength of this approach is its ability to dynamically model the RNA temporal measurements. The approach developed paves the way for inferring regulatory processes in many complex cellular processes.

systems biology↗

bioRxiv2022

PP4 inhibition sensitizes ovarian cancer to NK cell-mediated cytotoxicity via STAT1 activation and inflammatory signaling

BackgroundIncreased infiltration of T cells into ovarian tumors has been repeatedly shown to be predictive of enhanced patient survival. However, despite the evidence of an active immune response in ovarian cancer (OC), the frequency of responses to immune checkpoint blockade (ICB) therapy in OC is much lower than other cancer types. Recent studies have highlighted that deficiencies in the DNA damage response (DDR) can drive increased genomic instability and tumor immunogenicity, which leads to enhanced responses to ICB. Protein phosphatase 4 (PP4) is a critical regulator of the DDR; however, its potential role in anti-tumor immunity is currently unknown. ResultsOur results show that the PP4 inhibitor, fostriecin, combined with carboplatin leads to increased carboplatin sensitivity, DNA damage, and micronuclei formation. Using multiple ovarian cancer cell lines, we show that PP4 inhibition or PPP4C knockdown combined with carboplatin triggers inflammatory signaling via NF{kappa}B and STAT1 activation. This resulted in increased expression of the pro-inflammatory cytokines and chemokines: CCL5, CXCL10, and IL6. In addition, IFNB1 expression was increased suggesting activation of the type I interferon response. Conditioned media from OC cells treated with the combination of PP4 inhibitor and carboplatin significantly increased migration of both CD8 T cell and NK cells over carboplatin treatment alone. Knockdown of STING in OC cells significantly abrogated the increase in CD8 T cell migration induced by PP4 inhibition. Co-culture of NK-92 cells and OC cells with PPP4C or PPP4R3B knockdown resulted in strong induction of NK cell activation as measured by IFN-{gamma} levels. Further, we also observed increased degranulation and NK cell-mediated cytotoxicity against OC cells with PPP4C or PPP4R3B knockdown. ConclusionsOur work has identified a role for PP4 inhibition in promoting inflammatory signaling and enhanced immune cell effector function. These findings support the further investigation of PP4 inhibitors to enhance chemo-immunotherapy for ovarian cancer treatment.

cancer biology↗

bioRxiv2021

Sequestration of histidine kinases by non-cognate response regulators establishes a threshold level of stimulation for bacterial two-component signaling

Two-component signaling systems (TCSs) in bacteria are often positively auto-regulated, where the histidine kinase (HK) and response regulator (RR) proteins comprising a TCS are expressed downstream of the signal they transduce. This auto-regulation improves the sensitivity of the TCS to stimuli and amplifies adaptive responses. The downside, however, is that the TCS may mount disproportionately large responses to weak or fleeting signals. How bacteria prevent such disproportionate responses is not known. Here, we show that sequestration of phosphorylated HKs by non-cognate RRs serves as a design to prevent such disproportionate responses. Using TCSs of M. tuberculosis as model systems, we found that with every one of the five HKs we studied, there was at least one non-cognate RR with higher affinity than that of the cognate RR for the HK. Phosphorylated HKs would thus preferentially bind the non-cognate RRs, suppressing signal transduction through the cognate pathways, which we demonstrated in vitro. Using mathematical modeling of TCS signaling in vivo, we predicted that this sequestration would introduce a threshold level of stimulation for a significant response, preventing responses to signals below this threshold. Finally, we showed in vivo using tunable expression systems in M. bovis that upregulation of a higher affinity non-cognate RR substantially suppressed the output from the cognate TCS pathway, presenting strong evidence of sequestration by non-cognate RRs as a design to regulate TCS signaling. Blocking this sequestration may be a novel intervention strategy, as it would compromise bacterial fitness by letting it respond unnecessarily to signals.

systems biology↗

bioRxiv2021

HIV-1 Vif protein is stabilized by AKT-mediated phosphorylation to enhance APOBEC3G degradation

HIV-1 virus has to counter anti-viral restriction factors for its successful replication after its entry in the cell. The host-pathogen dynamics operate as soon as HIV-1 interacts with the cell. HIV-1 Vif has been known for its role in degradation of APOBEC3G; a cytosine deaminase which leads to hyper mutations in the viral DNA leading to aberrant viral replication. The cellular proteins regulating the intracellular HIV-1 Vif protein levels can have profound impact on HIV-1 pathogenesis. MDM2 is known to induce degradation of Vif with subsequent effects on APOBEC3G. Here, we have identified AKT/PKB as one of the crucial regulators of HIV-1 Vif protein. The rationale for selecting Vif as a target substrate for AKT was the presence of RMRINT motif in it, which is similar to the AKT phosphorylation motif RxRxxS/T. Immunoprecipitation assay and Kinase assay revealed that AKT and Vif interact strongly with each other and Vif is phosphorylated at T20 position by AKT. This phosphorylation stabilizes HIV-1 Vif while Vif mutant T20A degrades faster. Moreover, use of dominant negative form of AKT (KD-AKT) and AKT inhibitors were found to destabilise Vif and increase its K48-ubiquitination profile. The consequences of this AKT-Vif interplay were also validated on APOBEC3G degradation, a target of Vif. AKT inhibition was found to restore APOBEC3G levels. This process can be interpreted as a strategy used by virus to prevent MDM2 mediated Vif degradation; AKT stabilises Mdm2, which then targets Vif for degradation but at the same time AKT stabilises Vif by phosphorylating it. Thus, AKT mediated stabilization of Vif might compensate for its degradation by MDM2. This study can have significant implications as HIV-1 Tat protein and growth factors like insulin activate PI3-K/AKT Kinase pathway and can potentially affect Vif and APOBEC3G protein levels and hence HIV-1 pathogenesis.

cell biology↗

bioRxiv2021

Decentralized Brain Age Estimation using MRI Data

Recent studies have demonstrated that neuroimaging data can be used to predict brain age, as it captures information about the neuroanatomical and functional changes the brain undergoes during development and the aging process. However, researchers often have limited access to neuroimaging data because of its challenging and expensive acquisition process, thereby limiting the effectiveness of the predictive model. Decentralized models provide a way to build more accurate and generalizable prediction models, bypassing the traditional data-sharing methodology. In this work, we propose a decentralized method for brain age estimation and evaluate it on three different feature sets, including both volumetric and voxelwise structural MRI data as well as resting functional MRI data. The results demonstrate that a decentralized brain age model can achieve similar performance compared to the models trained with all the data in one location.

neuroscience↗

bioRxiv2019

Modeling how early passive immunization with broadly neutralizing antibodies elicits lasting control of SHIV infection

Antiretroviral therapy (ART) for HIV-1 infection is life-long. Stopping therapy typically leads to the reignition of infection and progressive disease. In a major breakthrough, recent studies have shown that early initiation of ART can lead to sustained post-treatment control of viremia, raising hopes of long-term HIV-1 remission. ART, however, elicits post-treatment control in a small fraction of individuals treated. Strikingly, passive immunization with broadly neutralizing antibodies (bNAbs) of HIV-1 early in infection was found recently to elicit long-term control in a majority of SHIV-infected macaques, suggesting that HIV-1 remission may be more widely achievable. The mechanisms underlying the control elicited by bNAb therapy, however, remain unclear. Untreated infection typically leads to progressive disease. We hypothesized that viremic control represents an alternative but rarely realized outcome of the infection and that early bNAb therapy triggers a dynamical switch to this outcome. To test this hypothesis, we constructed a model of viral dynamics with bNAb therapy and applied it to analyse clinical data. The model fit quantitatively the complex longitudinal viral load data from macaques that achieved lasting control. The model predicted, consistently with our hypothesis, that the underlying system exhibited bistability, indicating two potential outcomes of infection. The first had high viremia, weak cytotoxic effector responses, and high effector exhaustion, marking progressive disease. The second had low viremia, strong effector responses, and low effector exhaustion, indicating lasting viremic control. Further, model predictions suggest that early bNAb therapy elicited lasting control via pleiotropic effects. bNAb therapy lowers viremia, which would also limit immune exhaustion. Simultaneously, it can improve effector stimulation via cross-presentation. Consequently, viremia may resurge post-therapy, but would encounter a primed effector population and eventually get controlled. ART suppresses viremia but does not enhance effector stimulation, explaining its limited ability to elicit post-treatment control relative to bNAb therapy. Author SummaryIn a remarkable advance in HIV cure research, a recent study showed that 3 weekly doses of HIV-1 broadly neutralizing antibodies (bNAbs) soon after infection kept viral levels controlled for years in most macaques treated. If translated to humans, this bNAb therapy may elicit a functional cure, or long-term remission, of HIV-1 infection, eliminating the need for life-long antiretroviral therapy (ART). How early bNAb therapy works remains unknown. Here, we elucidate the mechanism using mathematical modeling and analysis of in vivo data. We predict that early bNAb therapy suppresses viremia, which reduces exhaustion of cytotoxic effector cells, and enhances antigen uptake and effector stimulation. Collectively, these effects drive infection to lasting control. Model predictions based on these effects fit in vivo data quantitatively. ART controls viremia but does not improve effector stimulation, explaining its weaker ability to induce lasting control post-treatment. Our findings may help improve strategies for achieving functional cure of HIV-1 infection.

immunology↗