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Subramanian, S.

Publications and source records attributed to Subramanian, S..

At least 91 records · Page 5Linked to original sources
bioRxiv2020

Disruption of a GATA2, TAL1, ERG regulatory circuit promotes erythroid transition in healthy and leukemic stem cells

Changes in gene regulation and expression govern orderly transitions from hematopoietic stem cells to terminally differentiated blood cell types. These transitions are disrupted during leukemic transformation but knowledge of the gene regulatory changes underpinning this process is elusive. We hypothesised that identifying core gene regulatory networks in healthy hematopoietic and leukemic cells could provide insights into network alterations that perturb cell state transitions. A heptad of transcription factors (LYL1, TAL1, LMO2, FLI1, ERG, GATA2, RUNX1) bind key hematopoietic genes in human CD34+ haematopoietic stem and progenitor cells (HSPCs) and have prognostic significance in acute myeloid leukemia (AML). These factors also form a densely interconnected circuit by binding combinatorially at their own, and each others, regulatory elements. However, their mutual regulation during normal haematopoiesis and in AML cells, and how perturbation of their expression levels influences cell fate decisions remains unclear. Here, we integrated bulk and single cell data and found that the fully connected heptad circuit identified in healthy HSPCs persists with only minor alterations in AML, and that chromatin accessibility at key heptad regulatory elements was predictive of cell identity in both healthy progenitors and in leukemic cells. The heptad factors GATA2, TAL1 and ERG formed an integrated sub-circuit that regulates stem cell to erythroid transition in both healthy and leukemic cells. Components of this triad could be manipulated to facilitate erythroid transition providing a proof of concept that such regulatory circuits could be harnessed to promote specific cell type transitions and overcome dysregulated haematopoiesis.

cancer biology↗
bioRxiv2020

Naegleria fowleri: protein structures to facilitate drug discovery for the deadly, pathogenic free-living amoeba

Naegleria fowleri is a pathogenic, thermophilic, free-living amoeba which causes primary amebic meningoencephalitis (PAM). Penetrating the olfactory mucosa, the brain-eating amoeba travels along the olfactory nerves, burrowing through the cribriform plate to its destination: the brains frontal lobes. The amoeba thrives in warm, freshwater environments, with peak infection rates in the summer months and has a mortality rate of approximately 97%. A major contributor to the pathogens high mortality is the lack of sensitivity of N. fowleri to current drug therapies, even in the face of combination-drug therapy. To enable rational drug discovery and design efforts we have pursued protein production and crystallography-based structure determination efforts for likely drug targets from N. fowleri. N. fowleri genes were selected if they had homology to drug targets listed in Drug Bank or were nominated by primary investigators engaged in N. fowleri research. In 2017, 178 N. fowleri protein targets were queued to the Seattle Structural Genomics Center of Infectious Disease (SSGCID) pipeline, and to date 89 soluble recombinant proteins and 19 unique target structures have been produced. Many of the new protein structures are potential drug targets and contain structural differences compared to their human homologs, which could allow for the development of pathogen-specific inhibitors. Five of the structures were analyzed in more detail, and four of five show promise that selective inhibitors of the active site could be found. The 19 solved crystal structures build a foundation for future work in combating this devastating disease by encouraging further investigation to stimulate drug discovery for this neglected pathogen.

molecular biology↗
bioRxiv2020

A Structured Professional Development Curriculum for Postdoctoral Fellows Leads to Recognized Knowledge Growth

Postdoctoral training enables research independence and professional readiness. National reports have emphasized professional development as a critical component of this training period. In response, many institutions are establishing transferable skills training workshops for postdocs; however, the lack of structured programs and an absence of methods to assess outcomes beyond participant satisfaction surveys are critical gaps in postdoctoral training. To address these shortcomings, we took the approach of structured programming and developed a method for controlled assessment of outcomes. Our program You3 (You, Your Team, Your Project), co-designed by postdoctoral fellows, focused on a structured array of management and leadership skills agnostic of ultimate career path(s). We then measured outcomes in a controlled manner, by systematically comparing perceived knowledge and growth of participants with non-participants as the control group. You3 participants discern greater growth, independent of number of years in training, in competencies overall compared to the control group. This growth was shown by multiple criteria including self-reporting and associative analysis. Correspondingly, You3 participants reported greater knowledge in 75% of the modules when compared to controls. These data indicate that structured learning, where postdocs commit to a curriculum via a cohort-structure, leads to positive outcomes and provides a framework for programs to assess outcomes in a rigorous manner.

scientific communication and education↗
bioRxiv2020

Remote Learning Barriers and Opportunities for Graduate Student and Postdoctoral Learners in Career and Professional Skill Development: A Case Study

Career and professional development competencies are critical for biomedical PhD and postdoctoral training. In the current educational landscape, programs that meet these competencies are offered and attended in an ad hoc manner. During the COVID-19 pandemic and the accompanying switch to virtual learning, our team observed a surge in interest for our weekly non-sequential programs. In this study, we surveyed our learners to better understand motivators for attending these programs during the pandemic and to identify barriers for participating in such events before and during Work-From-Home. Our data indicate that conflict with research responsibilities, time spent to get to the event location, and planning time to attend are all significant barriers to engagement. Notably, feelings of being overwhelmed, which increased slightly during the pandemic, stood out as an identified barrier. Per our results, the virtual format was an attraction. While 58% of respondents would prefer to access professional development programs virtually in the future, almost 42% indicated a preference for in-person events when normalcy resumes as the physical presence of an instructor and of peers result in a deeper engagement. Our collective analysis here suggests that learners will benefit from a hybrid or combination of synchronous and asynchronous career and professional development programming in the future, even post-pandemic, to reduce identified barriers. Alongside hybrid learning engagements, we strongly recommend structured time for learners to enhance their professional competencies, enabled by a commitment from departments and faculty mentors to enable equity in professional skill building and fostering lifelong growth mindset.

scientific communication and education↗
bioRxiv2020

The transcriptome of Balamuthia mandrillaris trophozoites for structure-based drug design

Balamuthia mandrillaris, a pathogenic free-living amoeba (FLA), causes cutaneous skin lesions as well as the brain-eating disease: Balamuthia granulomatous amoebic encephalitis (GAE). These diseases, and diseases caused by other pathogenic FLA, Naegleria fowleri or Acanthamoeba species, are minimally studied from a drug discovery perspective; few targets have been validated or characterized at the molecular level, and little is known about the biochemical pathways necessary for parasite survival. Chemotherapies for CNS disease caused by B. mandrillaris require vast improvement. Current therapeutics are limited to a small number of drugs that were previously discovered in the last century through in vitro testing or identified after use in the small pool of surviving reports. Using our recently published methodology to identify potentially useful therapeutics, we screened a collection of 85 compounds that have previously been reported to have antiparasitic activity. We identified 59 compounds that impacted growth at concentrations below 220 M. Since there is no fully annotated genome or proteome, we used RNA-Seq to reconstruct the transcriptome of B. mandrillaris and locate the coding sequences of the specific genes potentially targeted by the compounds identified to inhibit trophozoite growth. We determined the sequence of 17 of these target genes and obtained expression clones for 15 that we validated by direct sequencing.

genomics↗
bioRxiv2020

Induction of Muscle Regenerative Multipotent Stem Cells from Human Adipocytes by PDGF-AB and 5-Azacytidine.

Terminally differentiated murine osteocytes and adipocytes can be reprogrammed using platelet-derived growth factor-AB and 5-Azacytidine into multipotent stem cells with stromal cell characteristics. To generate a product that is amenable for therapeutic application, we have modified and optimised culture conditions to reprogram human adipocytes into induced multipotent stem cells (iMS) and expand them in vitro. The basal transcriptomes of adipocyte-derived iMS cells and matched adipose-tissue-derived mesenchymal stem cells were remarkably similar. However, there were distinct changes in histone modifications and CpG methylation at cis-regulatory regions consistent with an epigenetic landscape that was primed for tissue development and differentiation. In a non-specific tissue injury xenograft model, iMS cells contributed directly to new muscle, bone, cartilage and blood vessels with no evidence of teratogenic potential. In a cardiotoxin muscle injury model, iMS cells contributed specifically to satellite cells and myofibres without ectopic tissue formation. Taken together, human adipocyte derived iMS cells regenerate tissues in a context dependent manner without ectopic or neoplastic growth.

cell biology↗
bioRxiv2020

In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N=80 samples from persons with RT-PCR confirmed SARS-CoV2 infection), and a specificity of 97.2% (N=106 control samples).

bioinformatics↗
bioRxiv2020

A Model-Based Approach for Pulse Selection from Electrodermal Activity

ObjectiveThe goal of this work was to develop a physiology-based paradigm for pulse selection from electrodermal activity (EDA) data. MethodsWe aimed to use insight about the integrate-and-fire physiology of sweat gland bursts, which predicts inverse Gaussian inter-pulse interval structure. At the core of our paradigm is a subject-specific amplitude threshold selection process for pulses based on the statistical properties of four right-skewed models including the inverse Gaussian. These four models differ in their tail behavior, which reflects sweat gland physiology to varying degrees. By screening across thresholds and fitting all four models, we selected for heavier tails that reflect inverse Gaussian-like structure and verified the pulse selection with a goodness-of-fit analysis. ResultsWe tested our paradigm on two different subject cohorts recorded during different experimental conditions and using different equipment. In both cohorts, our method robustly and consistently recovered pulses that captured the inverse Gaussian-like structure predicted by physiology, despite large differences in noise level of the data. In contrast, an established EDA analysis paradigm, which assumes a constant amplitude threshold across all data, was unable to separate pulses from noise. ConclusionWe present a computationally efficient, statistically rigorous, and physiology-informed paradigm for pulse selection from EDA data that is robust across individuals and experimental conditions yet adaptable to changes in noise level. SignificanceThe robustness of our paradigm and its basis in physiology move EDA closer to serving as a clinical marker for sympathetic activity in diverse conditions such as pain, anxiety, depression, and sleep.

physiology↗
bioRxiv2020

Comparative analysis of genome-wide DNA methylation identifies patterns that associate with conserved transcriptional programs in osteosarcoma.

Osteosarcoma is an aggressive tumor of the bone that primarily affects young adults and adolescents. Osteosarcoma is characterized by genomic chaos and heterogeneity. While inactivation of tumor suppressor p53 TP53 is nearly universal other high frequency mutations or structural variations have not been identified. Despite this genomic heterogeneity, key conserved transcriptional programs associated with survival have been identified across human, canine and induced murine osteosarcoma. The epigenomic landscape, including DNA methylation, plays a key role in establishing transcriptional programs in all cell types. The role of epigenetic dysregulation has been studied in a variety of cancers but has yet to be explored at scale in osteosarcoma. Here we examined genome-wide DNA methylation patterns in 24 human and 44 canine osteosarcoma samples identifying groups of highly correlated DNA methylation marks in human and canine osteosarcoma samples. We also link specific DNA methylation patterns to key transcriptional programs in both human and canine osteosarcoma. Building on previous work, we built a DNA methylation-based measure for the presence and abundance of various immune cell types in osteosarcoma. Finally, we determined that the underlying state of the tumor, and not changes in cell composition, were the main driver of differences in DNA methylation across the human and canine samples. SignificanceThis is the first large scale study of DNA methylation in osteosarcoma and lays the ground work for the exploration of DNA methylation programs that help establish conserved transcriptional programs in the context of different genomic landscapes.

cancer biology↗
bioRxiv2020

Tumor secreted extracellular vesicles regulate T-cell costimulation and can be manipulated to induce tumor-specific T-cell responses

Tumor intrinsic factors negatively regulate tumor immune cell infiltration and function. Deciphering the underlying mechanisms is critical to improving immunotherapy in cancers. Our analyses of human colorectal cancer (CRC) immune profiles and tumor-immune cell interactions revealed that tumor cell secreted extracellular vesicles (TEVs) induced immunosuppression in CRC. Specifically, TEVs containing microRNA miR-424 suppressed the CD28-CD80/86 costimulatory pathway in tumor infiltrating T cells and dendritic cells. Modified TEVs with miR-424 knocked down enhanced T-cell mediated antitumor immune response in CRC tumor models and increased the response to immune checkpoint blockade therapies (ICBT). Intravenous injections of modified TEVs induced tumor antigen specific immune responses. Moreover, injections of modified TEVs boosted the ICBT efficacy in CRC models that mimic treatment refractory late-stage disease. Collectively, we demonstrate a critical role for TEVs in antitumor immune regulation and immunotherapy response, which could be developed as a novel treatment for ICBT resistant human CRC.

cancer biology↗
bioRxiv2020

Point Process Temporal Structure Characterizes Electrodermal Activity

Electrodermal activity (EDA) is a read-out of the bodys sympathetic nervous system measured as sweat-induced changes in the electrical conductance properties of the skin. There is growing interest in using EDA to track physiological conditions such as stress levels, sleep quality and emotional states. Standardized EDA data analysis methods are readily available. However, none considers two established physiological features of EDA: 1) sympathetically mediated pulsatile changes in skin sweat measured as EDA resemble an integrate-and-fire process; 2) inter-pulse interval times vary depending upon the local physiological state of the skin. Based on the anatomy and physiology that underlie feature 1, we postulate that inverse Gaussian probability models would accurately describe EDA inter-pulse intervals. Given feature 2, we postulate that under fluctuating local physiological states, the inter-pulse intervals would follow mixtures of inverse Gaussian models, that can be represented as lognormal models if the conditions favor longer intervals (heavy tails) or by gamma models if the conditions favor shorter intervals (light tails). To assess the validity of these probability models we recorded and analyzed EDA measurements in 11 healthy volunteers during 1 to 2 hours of quiet wakefulness. We assess the tail behavior of the probability models by computing their settling rates. All data series were accurately described by one or more of the models: two by inverse Gaussian models; five by lognormal models and three by gamma models. These probability models suggest a highly succinct point process framework for real-time tracking of sympathetically-mediated changes in physiological state.

neuroscience↗
bioRxiv2019

Gene regulatory networks associated with lateral root and nodule development in soybean

Legume plants such as soybean produce two major types of root lateral organs, lateral roots and root nodules. A robust computational framework was developed to predict potential gene regulatory networks (GRNs) associated with root lateral organ development in soybean. A genome-scale expression dataset was obtained from soybean root nodules and lateral roots and subjected to biclustering using QUBIC. Biclusters (BCs) and transcription factor (TF) genes with enriched expression in lateral root tissues were converged using different network inference algorithms to predict high confident regulatory modules that are repeatedly retrieved in different methods. The ranked combination of results from all different network inference algorithms into one ensemble solution identified 21 GRN modules of 182 co-regulated genes networks potentially involved in root lateral organ development stages in soybean. The pipeline correctly predicted previously known nodule- and LR-associated TFs including the expected hierarchical relationships. The results revealed high scorer AP2, GRF5, and C3H co-regulated GRN modules during early nodule development; and GRAS, LBD41, and ARR18 co-regulated GRN modules late during nodule maturation. Knowledge from this work supported by experimental validation in the future is expected to help determine key gene targets for biotechnological strategies to optimize nodule formation and enhance nitrogen fixation.

plant biology↗
bioRxiv2019

Two distinct mechanisms of small molecule inhibition of LpxA acyltransferase essential for lipopolysaccharide biosynthesis

The lipopolysaccharide biosynthesis pathway is considered an attractive drug target against the rising threat of multidrug-resistant Gram-negative bacteria. Here, we report two novel small-molecule inhibitors (compounds 1 and 2) of the acyltransferase LpxA, the first enzyme in the lipopolysaccharide biosynthesis pathway. We show genetically that the antibacterial activities of the compounds against efflux-deficient Escherichia coli are mediated by LpxA inhibition. Consistently, the compounds inhibited the LpxA enzymatic reaction in vitro. Intriguingly, using biochemical, biophysical, and structural characterization, we reveal two distinct mechanisms of LpxA inhibition; compound 1 is a substrate-competitive inhibitor targeting apo LpxA and compound 2 is an uncompetitive inhibitor targeting the LpxA-product complex. Compound 2 exhibited more favorable biological and physicochemical properties than compound 1, and was optimized using structural information to achieve improved antibacterial activity against wild type E. coli. These results show that LpxA is a promising antibacterial target and imply the advantages of targeting enzyme-product complexes in drug discovery.

biochemistry↗
bioRxiv2019

Frequency of MicroRNA Response Elements Identifies Pathologically Relevant Signaling Pathways in Cancers

Complex interactions between mRNAs and microRNAs influence cellular functions. The interactions between mRNA and microRNAs also determine the post-transcriptional availability of free mRNAs and unbound microRNAs. The microRNAs bind to one or more microRNA Response Elements (MREs) predominantly located on the 3untranslated regions (3UTR) of mRNAs. In this study, we leveraged MRE sites and their frequencies in transcriptomes of cancer and matched normal tissues to obtain insights into disease-specific interactions between mRNAs and microRNAs. Toward this, we developed a novel bioinformatics method called ReMIx that utilizes RNA-Seq data to quantify MRE frequencies at 3UTR of genes across the transcriptome. We applied ReMIx to The Cancer Genome Atlas (TCGA) Triple Negative (TN) breast cancer tumor-normal adjacent pairs (N=13) and identified distinctly and differentially expressed MREs specific to the TN tumors. Novel data generated by ReMIx identified candidate mRNAs and microRNAs in the MAPK signaling cascade of the TN tumors. We further analyzed the MAPK endogenous RNA network to establish regulatory microRNA partners, along with interacting protein-coding mRNAs that influence and modulate MAPK signaling in TN breast cancers.

bioinformatics↗
bioRxiv2019

RAS Internal Tandem Duplication Disrupts GAP-binding to Activate Oncogenic Signaling

Molecular testing of oncogenic RAS mutations in colorectal cancer (CRC) have led to increased identification of mutations in patients with CRC. NRAS-mutated CRC has not been well characterized because it is less common (<6%) than KRAS mutations. Here, we report a novel 10 amino acid internal tandem duplication (ITD) in NRAS, which disrupts the switch II domain, in a patient with widely disseminated CRC. Hotspot next generation sequencing of a brain metastasis identified the NRAS ITD and a TP53 missense mutation (p.P275F). Whole exome sequencing of the primary tumor and two metastatic lesions (lung and brain) confirmed that the NRAS ITD and TP53 mutation were conserved between the primary tumor and both metastatic tumors, and identified an additional pathogenic mutation in CSMD1 (a tumor suppressor gene). Structural biology and biochemical analyses demonstrated that the NRAS ITD prevented binding to GAP protein, leading to sustained RAS activation, increased interaction with RAF, and downstream MAPK activation. Additionally, we provide the first crystal structure of the RAS ITD. In conclusion, these studies indicate that the NRAS ITD was the probable primary driver mutation of this aggressive CRC. Identical or biologically similar ITDs in NRAS and KRAS may be rare drivers of CRC and other aggressive malignancies.

molecular biology↗
bioRxiv2019

Temporal distribution of deleterious variations influences the estimation of FST

Estimating the extent of genetic differentiation between populations is an important measure in population genetics, ecology and evolutionary biology. Fixation index or FST is an important measure, which is routinely used to quantify this. Previous studies have shown that FST estimated for selectively constrained regions was significantly lower than that estimated for neutral regions. By deriving the theoretical relationship between FST at neutral and constrained sites we show that an excess in the fraction of deleterious variations segregating within populations compared to that segregates between populations is the cause for the reduction in FST estimated at constrained sites. Using whole genome data, our results revealed that the magnitude of reduction in FST estimates obtained for selectively constrained regions was much higher for distantly related populations compared to those estimated for closely related pairs. For example, the reduction was 49% for comparison between European-African populations, 31% for European-Asian comparison, 16% for the Northern-Southern European pair and only 4% for the comparison involving two Southern European (Italian and Spanish) populations. Since deleterious variants are purged over time due to purifying selection, their contribution to the among population diversity at constrained sites decreases with the increase in the divergence between populations. However, within population diversity remain the same for all pairs compared above and therefore FST estimated at constrained sites for distantly related populations are much smaller than those estimated for closely related populations. Our results suggest that the level of population divergence should be considered when comparing constrained site FST estimates obtained for different pairs of populations.

genetics↗
bioRxiv2019

Tumor-draining lymph nodes resection and chemotherapy have diverse impacts on cancer immunotherapies

Immunotherapies are used as adjuvant therapies for cancers. However, knowledge of how traditional cancer treatments affect immunotherapies is limited. Using mouse models, we demonstrate that tumor-draining lymph nodes (TdLNs) are critical for tumor antigen-specific T-cell response. However, removing TdLNs concurrently with established primary tumors did not affect the immune checkpoint blockade (ICB) response on localized secondary tumor due to immunotolerance in TdLNs and distribution of antigen-specific T cells in peripheral lymphatic organs. Notably, treatment response improved with sequential administration of 5-fluorouracil (5-FU) and ICB compared to concurrent administration of ICB with 5-FU. Immune profiling revealed that using 5-FU as induction treatment increased tumor visibility to immune cells, decreased immunosuppressive cells in the tumor microenvironment, and limited chemotherapy-induced T-cell depletion. We show that the effect of traditional cytotoxic treatment, not TdLNs, influences immunotherapy response in localized secondary tumors. We postulate essential considerations for successful immunotherapy strategies in clinical conditions. Graphic abstractThe effects of tumor-draining lymph nodes (TdLNs) resection and a combination of cytotoxic chemotherapy on immune checkpoint blockade therapies are evaluated in this study. TdLNs resection was adverse in eliciting an antitumor immune response in early-stage tumors, but not in late-stage tumors. Further, sequential treatments with cytotoxic chemotherapy and immunotherapy showed better tumor control compared to concurrent combinatorial treatments.

cancer biology↗