Biology subjects

Saha, A.

Publications and source records attributed to Saha, A..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

IL6 mediated cFLIP downregulation increases the migratory and invasive potential of triple negative breast cancer cell line

c-FLIP (cellular FLICE-Like Inhibitor of Apoptotic protein) which belongs to the negative regulators of the death receptor pathway, control apoptosis in a number of cancers. literatures suggest that its overexpression facilitate cancer progression and also helps in the drug resistance. However, there is a very few data available to show how it control metastasis. Moreover, how cFLIP is regulated during the progression of cancer into advanced stage and its mechanism of action on tumor cell migration and invasion is yet to be known. Our TCGA data analysis has shown that cFLIP is downregulated in many cancers, including breast cancer, especially at the later stages. when, we analysed and compared early-stage breast carcinoma cell line MCF7 (luminal) and advanced stage triple negative cell line MDAMB-231, which is highly metastatic, we found a negative correlation between cFLIP expression and metastasis. Our results indicated that Il6, one of the most prominent cytokines inside tumor microenvironment, activated p38 and the later helped in cFLIP downregulation in MDA-MB-231 cell line. Moreover, we have found that cFLIP negatively regulated autophagy and this autophagy downregulation resulted in decrease in metastasis. Thus, we have shown, for the first time, a complete interconnecting pathway in which IL6 mediated p38 activation directly influences metastasis by regulating autophagy via cFLIP downregulation.

cancer biology↗

bioRxiv2023

Overlapping and Distinct Mechanisms of Effective Neoantigen Cancer Vaccines and Immune Checkpoint Therapy

The goal of therapeutic cancer vaccines and immune checkpoint therapy (ICT) is to eliminate cancer by expanding and/or sustaining T cells with anti-tumor capabilities. However, whether cancer vaccines and ICT enhance anti-tumor immunity by distinct or overlapping mechanisms remains unclear. Here, we compared effective therapeutic tumor-specific mutant neoantigen (NeoAg) cancer vaccines with anti-CTLA-4 and/or anti-PD-1 ICT in preclinical models. Both NeoAg vaccines and ICT induce expansion of intratumoral NeoAg-specific CD8 T cells, though the degree of expansion and acquisition of effector activity was much more substantial following NeoAg vaccination. Further, we found that NeoAg vaccines are particularly adept at inducing proliferating and stem-like NeoAg-specific CD8 T cells. Single cell T cell receptor (TCR) sequencing revealed that TCR clonotype expansion and diversity of NeoAg-specific CD8 T cells relates to their phenotype and functional state associated with specific immunotherapies employed. Effective NeoAg vaccines and ICT required both CD8 and CD4 T cells. While NeoAg vaccines and anti-PD-1 affected the CD4 T cell compartment, it was to less of an extent than observed with anti-CTLA-4, which notably induced ICOS+Bhlhe40+ Th1-like CD4 T cells and, when combined with anti-PD-1, a small subset of Th2-like CD4 T cells. Although effective NeoAg vaccines or ICT expanded intratumoral M1-like iNOS+ macrophages, NeoAg vaccines expanded rather than suppressed (as observed with ICT) M2-like CX3CR1+CD206+ macrophages, associated with the vaccine adjuvant. Further, combining NeoAg vaccination with ICT induced superior efficacy compared to either therapy in isolation, highlighting the utility of combining these modalities to eliminate cancer. HighlightsO_LINeoAg cancer vaccines utilize distinct mechanisms from CTLA-4 or PD-1 ICT C_LIO_LINeoAg vaccines induce TCF1+ stem-like and proliferating NeoAg-specific CD8 T cells C_LIO_LICD8 TCR clonotype expansion relates to phenotype and functional state associated with immunotherapy C_LIO_LINeoAg vaccines induce partially distinct macrophage remodeling from ICT C_LIO_LINeoAg vaccines synergize with ICT, exceeding combination CTLA-4/PD-1 ICT efficacy C_LI

immunology↗

bioRxiv2023

Differential Carbonic Anhydrase Activities Control EBV-Induced B-Cell Transformation and Lytic Cycle Reactivation

Epstein-Barr virus (EBV) contributes to [~]1% of all human cancers including several B-cell neoplasms. A characteristic feature of EBV life cycle is its ability to transform metabolically quiescent B-lymphocytes into hyperproliferating B-cell blasts with the establishment of viral latency, while intermittent lytic cycle induction is necessary for the production of progeny virus. Our RNA-Seq analyses of both latently infected naive B-lymphocytes and transformed B-lymphocytes upon lytic cycle replication indicate a contrasting expression pattern of a membrane-associated carbonic anhydrase isoform CA9, an essential component for maintaining cell acid-base homeostasis. We show that while CA9 expression is transcriptionally activated during latent infection model, lytic cycle replication restrains its expression. Pharmacological inhibition of CA-activity using specific inhibitors retards EBV induced B-cell transformation, inhibits B-cells outgrowth and colony formation ability of transformed B-lymphocytes through lowering the intracellular pH, induction of cell apoptosis and facilitating degradation of CA9 transcripts. Reanalyses of ChIP-Seq data along with utilization of EBNA2 knockout virus and sh-RNA mediated knockdown of CA9 expression we further demonstrate that EBNA2 mediated CA9 transcriptional activation is essential for EBV latently infected B-cell survival. In contrast, during lytic cycle reactivation CA9 expression is transcriptionally suppressed by the key EBV lytic cycle transactivator, BZLF1 through its transactivation domain. Overall, our study highlights the dynamic alterations of CA9 expression and its activity in regulating pH homeostasis act as one of the major drivers for EBV induced B-cell transformation and subsequent B-cell lymphomagenesis.

microbiology↗

bioRxiv2023

PRIEST - Predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information

The dynamic evolution of the SARS-CoV-2 virus is largely driven by mutations in its genetic sequence, culminating in the emergence of variants with increased capability to evade host immune responses. Accurate prediction of such mutations is fundamental in mitigating pandemic spread and developing effective control measures. In this study, we introduce a robust and interpretable deep-learning approach called PRIEST. This innovative model leverages time-series viral sequences to foresee potential viral mutations. Our comprehensive experimental evaluations underscore PRIESTs proficiency in accurately predicting immune-evading mutations. Our work represents a substantial step forward in the utilization of deep-learning methodologies for anticipatory viral mutation analysis and pandemic response.

bioinformatics↗

bioRxiv2023

GATA-regulated transcriptional program dictate cell fate equilibrium to establish the maternal-fetal exchange interface and fetal development

The placenta establishes a maternal-fetal exchange interface to transport nutrients and gases between the mother and the fetus. Establishment of this exchange interface relies on the development of multinucleated syncytiotrophoblasts (SynT) from trophoblast progenitors and defect in SynT development often leads to pregnancy failure and impaired embryonic development. Here, we show that mouse embryos with conditional deletion of GATA2 and GATA3 in labyrinth trophoblast progenitors have underdeveloped placenta and die [~] embryonic day 9.5 (E9.5). Single cell RNA Seq (scRNA-Seq) analysis revealed excessive accumulation of multipotent labyrinth trophoblast progenitors upon conditional deletion of GATA factors. The GATA factor-deleted multipotent progenitors were unable to differentiate to matured SynTs. We also show that the GATA factor-mediated priming of trophoblast progenitors for SynT differentiation is a conserved event during human placentation. Loss of either GATA2 or GATA3 in cytotrophoblast (CTB)-derived human trophoblast stem cells (human TSCs) drastically inhibits SynT differentiation potential. Identification of GATA2 and GATA3 target genes along with comparative bioinformatics analyses revealed that GATA factors directly regulate hundreds of common genes in human TSCs, including genes that are essential for SynT development and implicated in preeclampsia and fetal growth retardation. Thus, our study uncovers a conserved molecular mechanism, in which coordinated function of GATA2 and GATA3 promote trophoblast progenitor-to-SynT commitment ensuring establishment of the maternal-fetal exchange interface.

developmental biology↗

bioRxiv2022

Proteomic Analysis Defines the Interactome of Telomerase in the Protozoan Parasite, Trypanosoma brucei

Telomerase is a ribonucleoprotein enzyme responsible for maintaining the telomeric end of the chromosome. The telomerase enzyme requires two main components to function: the telomerase reverse transcriptase (TERT) and the telomerase RNA (TR), which provides the template for telomeric DNA synthesis. TR is a long noncoding RNA, which forms the basis of a large structural scaffold upon which many accessory proteins can bind and form the complete telomerase holoenzyme. These accessory protein interactions are required for telomerase activity and regulation inside cells. The interacting partners of TERT have been well studied in yeast, human, and Tetrahymena models, but not in lower eukaryotes, including clinically relevant human parasites. Here, using the protozoan parasite, Trypanosoma brucei (T. brucei) as a model, we have identified the interactome of T. brucei TERT (TbTERT) using a mass spectrometry-based approach. We identified previously known and unknown interacting factors of TbTERT, highlighting unique features of T. brucei telomerase biology. These unique interactions with TbTERT, suggest mechanistic differences in telomere maintenance between T. brucei and other eukaryotes.

molecular biology↗

bioRxiv2022

Crystal structure and activity profiling of deubiquitinating inhibitors-bound to SARS-CoV-2 papain like protease revealed new allosteric sites for antiviral therapies

SARS-CoV-2 papain-like protease (PLpro) is a key antiviral target as it plays a dual role in viral replication and in modulation of innate immune responses by deubiquitinating or deISGylating host proteins. Thus, therapeutic targeting of PLpro serves as a two-pronged approach to abate SARS-CoV-2. Interestingly, PLpro shares structural and functional similarities with the cellular deubiquitinating enzymes (DUBs) and in this study this fact has been exploited to identify DUBs inhibitors that target the Ubiquitin/ISG15 binding site and the known catalytic substrate binding pocket of PLpro. Among these identified compounds, flupenthixol, lithocholic acid, teneligliptin, and linagliptin markedly inhibited the proteolytic activity of purified PLpro and demonstrated potent antiviral efficacies against SARS-CoV-2 infection in a dose dependent manner. Treatment with lithocholic acid and linagliptin suppressed the expression levels of inflammatory mediators, thereby, restoring immune responses. Crystal structures of SARS-CoV-2 PLpro in complex with linagliptin and with lithocholic acid determined in this study, revealed insights into the inhibition mechanism with unique interactions within the Ubiquitin/ISG15 binding site (S2 site; Phe69, His73, Asn128, His175) and the substrate binding cleft. Additionally, oral and intraperitoneal treatments with linagliptin increased survival, reduced lung viral load, and ameliorated histopathological damage in mouse-adapted model of SARS-CoV-2 infection. The study for the first time demonstrates a two-pronged strategy using DUB inhibitors that target the proteolytic activity of PLpro and simultaneously reinstates the hosts immune response against SARS-CoV-2.

molecular biology↗

bioRxiv2022

PD-L1 activity is associated with partial EMT and metabolic reprogramming in carcinomas

Immune evasion and metabolic reprogramming are hallmarks of cancer progression often associated with a poor prognosis and frequently present significant challenge for cancer therapies. Recent studies have emphasized on the dynamic interaction between immunosuppression and the dysregulation of energy metabolism in modulating the tumor microenvironment to promote cancer aggressiveness. However, a pan-cancer association among these two hallmarks, and a potent common driver for them - Epithelial-Mesenchymal Transition (EMT) - remains to be done. Here, our meta-analysis across 184 publicly available transcriptomic datasets as well as The Cancer Genome Atlas (TCGA) data reveals that an enhanced PD-L1 activity signature along with other immune checkpoint markers correlate positively with a partial EMT and elevated glycolysis signature but a reduced OXPHOS signature in many carcinomas. These trends were also recapitulated in single-cell RNA-seq time-course EMT induction data across cell lines. Furthermore, across multiple cancer types, concurrent enrichment of glycolysis and PD-L1 results in worse outcomes in terms of overall survival as compared to enrichment for only PD-L1 activity or expression. Our results highlight potential functional synergy among these interconnected axes of cellular plasticity in enabling metastasis and/or multi-drug resistance in cancer.

cancer biology↗

bioRxiv2022

An Alpha-helical Lid Guides the Target DNA toward Catalysis in CRISPR-Cas12a

CRISPR-Cas12a is a powerful RNA-guided genome-editing system, also emerging as a robust diagnostic tool that cleaves double-stranded DNA using only the RuvC domain. This opens an overarching question on how the spatially distant DNA target strand (TS) traverses toward the RuvC catalytic core. Here, continuous tens of microsecond-long molecular dynamics and free-energy simulations reveal that an -helical lid, located within the RuvC domain, plays a pivotal role in the traversal of the TS by anchoring the crRNA:TS hybrid and elegantly guiding the TS toward the RuvC core, as also corroborated by DNA cleavage experiments. In this mechanism, the REC2 domain pushes the crRNA:TS hybrid toward the core of the enzyme, while the Nuc domain aids the bending and accommodation of the TS within the RuvC core by bending inward. Understanding of this cardinal process in the functioning of Cas12a will enrich fundamental knowledge and facilitate further engineering strategies for genome-editing.

biophysics↗

bioRxiv2022

Decoding the Effects of Spike Receptor Binding Domain Mutations on Antibody Escape Abilities of Omicron Variants

Recent times witnessed an upsurge in the number of COVID cases which is primarily attributed to the emergence of several omicron variants, although there is substantial population vaccination coverage across the globe. Currently, many therapeutic antibodies have been approved for emergency usage. The present study critically evaluates the effect of mutations observed in several omicron variants on the binding affinities of different classes of RBD-specific antibodies using a combined approach of immunoinformatics and binding free energy calculations. Our binding affinity data clearly show that omicron variants achieve antibody escape abilities by incorporating mutations at the immunogenic hotspot residues for each specific class of antibody. K417N and Y505H point mutations are primarily accountable for the loss of class I antibody binding affinities. The K417N/Q493R/Q498R/Y505H combined mutant significantly reduces binding affinities for all the class I antibodies. E484A single mutation, on the other hand, drastically reduces binding affinities for most of the class II antibodies. E484A and E484A/Q493R double mutations cause a 33-38% reduction in binding affinity for the approved therapeutic monoclonal antibodies, Bamlanivimab (LY-CoV555). The Q498R RBD mutation observed across all the omicron variants can reduce ~12% binding affinity for REGN10987, a class III therapeutic antibody, and the L452R/Q498R double mutation causes a ~6% decrease in binding affinities for another class III therapeutic antibody, LY-CoV1404. Our data suggest that achieving the immune evasion abilities appears to be the selection pressure behind the emergence of omicron variants.

bioinformatics↗

bioRxiv2022

nnSVG: scalable identification of spatially variable genes using nearest-neighbor Gaussian processes

Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian processes. Our method (i) identifies genes that vary in expression continuously across the entire tissue or within a priori defined spatial domains, (ii) uses gene-specific estimates of length scale parameters within the Gaussian process models, and (iii) scales linearly with the number of spatial locations. We demonstrate the performance of our method using experimental data from several technological platforms and simulations. A software implementation is available at https://bioconductor.org/packages/nnSVG.

genomics↗

bioRxiv2022

Hippo Signaling Cofactor, WWTR1, at the Crossroads of Human Trophoblast Progenitor Self-Renewal and Differentiation.

Healthy progression of human pregnancy relies on cytotrophoblast progenitor (CTB) self-renewal and their differentiation towards multi-nucleated syncytiotrophoblasts (STBs) and invasive extravillous trophoblasts (EVTs). However, underlying molecular mechanisms that fine-tune CTB self-renewal or direct their differentiation towards STBs or EVTs during human placentation are poorly defined. Here, we show that hippo signaling cofactor WW Domain Containing Transcription Regulator 1 (WWTR1) is a master regulator of trophoblast fate choice during human placentation. Using human trophoblast stem cells (human TSCs), primary CTBs and human placental explants, we demonstrate that WWTR1 promotes self-renewal in human CTBs and is essential for their differentiation to EVTs. In contrast, WWTR1 prevents induction of STB fate in undifferentiated CTBs. Our single-cell RNA-sequencing analyses in first-trimester human placenta along with mechanistic analyses in human TSCs revealed that WWTR1 fine-tunes trophoblast fate by directly regulating Wnt signaling components. Importantly, our analyses of placentae from pathological pregnancies show that extreme preterm birth (gestational time [≤]28weeks) and intrauterine growth restriction along with preeclampsia (IUGR/PE) are often associated with loss of WWTR1 expression in CTBs. In summary, our findings establish a critical importance of WWTR1 at the crossroads of human trophoblast progenitor self-renewal vs. differentiation. It plays positive instructive roles to promote CTB self-renewal and EVT differentiation and safeguards undifferentiated CTBs from obtaining the STB fate. SIGNIFICANCEHuman pregnancy relies on formation of the transient organ placenta and trophoblast cells are the major building blocks of the placenta. A defect in trophoblast progenitor self-renewal or their differentiation is associated with either pregnancy loss or pathological pregnancies, yet underlying molecular mechanisms that regulate trophoblast differentiation are poorly understood. In this study, we discovered that WWTR1, a transcription cofactor and a component of conserved Hippo signaling pathway, optimizes trophoblast progenitor self-renewal and is essential for their differentiation into the invasive extravillous trophoblast cell lineage. Our findings establish WWTR1 as a critical regulator for success in human placentation and progression of a healthy pregnancy.

developmental biology↗

bioRxiv2022

FTY720 requires vitamin B12-TCN2-CD320 signaling in astrocytes to reduce disease in an animal model of multiple sclerosis

FTY720 (fingolimod) is a sphingosine 1-phosphate (S1P) receptor modulator and sphingosine analogue approved for multiple sclerosis (MS) therapy, which can functionally antagonize the S1P receptor, S1P1. Vitamin B12 (B12) deficiency produces neurological manifestations resembling MS. Here, we report a new mechanism where FTY720 suppresses neuroinflammation by regulating B12 metabolic pathways. Nuclear RNA-seq of c-Fos-activated astrocytes (called ieAstrocytes) from experimental autoimmune encephalomyelitis (EAE) spinal cords identified up-regulation of CD320, a transcobalamin 2 (TCN2)-B12 receptor, by S1P1 inhibition. CD320 was reduced in MS plaques. Deficiency of CD320 or dietary B12 worsened EAE and eliminated FTY720s efficacy, while concomitantly down-regulating type I interferon signaling. TCN2 functioned as a chaperone for FTY720 and sphingosine, which induced astrocytic CD320 internalization. An accompanying paper identified a requirement for astrocyte sphingosine kinases in FTY720 efficacy and its altered expression in MS brains, molecularly linking MS and B12 deficiency that can be accessed by sphingolipid/fingolimod metabolic pathways.

neuroscience↗

bioRxiv2021

Quantifying the patterns of metabolic plasticity and heterogeneity along the epithelial-hybrid-mesenchymal spectrum in cancer

Cancer metastasis is the leading cause of cancer-related mortality and the process of Epithelial to Mesenchymal Transition (EMT) is crucial for cancer metastasis. Either a partial or complete EMT have been reported to influence the metabolic plasticity of cancer cells in terms of switching among oxidative phosphorylation, fatty acid oxidation and glycolysis pathways. However, a comprehensive analysis of these major metabolic pathways their associations with EMT across different cancers is lacking. Here, we analyse more than 180 cancer cell datasets and show diverse associations of these metabolic pathways with the EMT status of cancer cells. Our bulk data analysis shows that EMT generally positively correlates with glycolysis but negatively with oxidative phosphorylation and fatty acid metabolism. These correlations are also consistent at the level of their molecular master regulators, namely AMPK and HIF1. Yet, these associations are shown to not be universal. Analysis of singlecell data of EMT induction shows dynamic changes along the different axes of metabolic pathways, consistent with general trends seen in bulk samples. Together, our results reveal underlying patterns of metabolic plasticity and heterogeneity as cancer cells traverse through the epithelial-hybrid-mesenchymal spectrum of states.

cancer biology↗

bioRxiv2021

QT-GILD: Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data

Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, for a combination of reasons (ranging from sampling biases to more biological causes, as in gene birth and loss), gene trees are often incomplete, meaning that not all species of interest have a common set of genes. Incomplete gene trees can potentially impact the accuracy of phylogenomic inference. We, for the first time, introduce the problem of imputing the quartet distribution induced by a set of incomplete gene trees, which involves adding the missing quartets back to the quartet distribution. We present QT-GILD, an automated and specially tailored unsupervised deep learning technique, accompanied by cues from natural language processing (NLP), which learns the quartet distribution in a given set of incomplete gene trees and generates a complete set of quartets accordingly. QT-GILD is a general-purpose technique needing no explicit modeling of the subject system or reasons for missing data or gene tree heterogeneity. Experimental studies on a collection of simulated and empirical data sets suggest that QT-GILD can effectively impute the quartet distribution, which results in a dramatic improvement in the species tree accuracy. Remarkably, QT-GILD not only imputes the missing quartets but it can also account for gene tree estimation error. Therefore, QT-GILD advances the state-of-the-art in species tree estimation from gene trees in the face of missing data. QT-GILD is freely available in open source form at https://github.com/pythonLoader/QT-GILD.

bioinformatics↗

bioRxiv2021

Cell Sex and Sex Hormones Modulate Kidney Glucose and Glutamine Metabolism in Health and Diabetes

Male sex is a risk factor for progression of diabetic kidney disease, but the reasons for this predilection are unclear. Here, we demonstrate that cell sex and sex hormones alter the metabolic phenotype of human proximal tubular epithelial cells (PTECs). Male PTECs displayed increased glycolysis, mitochondrial respiration, oxidative stress, apoptosis, and high glucose-induced injury, compared to female PTECs. This phenotype was enhanced by dihydrotestosterone (DHT) and linked to increased mitochondrial utilization of glucose and glutamine. Studies in vivo pointed towards increased glutamine anaplerosis in diabetic male kidneys. Male sex was linked to increased levels of glutamate, TCA cycle, and glutathione cycle metabolites, in PTECs and in the blood metabolome of healthy youth and youth with type 2 diabetes. Conversely, female PTECs displayed increased levels of pyruvate, glutamyl-cysteine, cysteinylglycine, and a higher GSH/GSSG ratio than male PTECs, indicative of enhanced redox homeostasis. Finally, we identified transcriptional mechanisms that control kidney metabolism in a sex-specific fashion. While X-linked demethylase KDM6A facilitated metabolic homeostasis in female PTECs, transcription factor HNF4A mediated the deleterious effects of DHT in male PTECs. This work uncovers the role of sex in glucose/glutamine metabolism, that may explain the roots of sex dimorphism in the healthy and diabetic kidney.

cell biology↗

bioRxiv2021

A Bayesian Precision Medicine Framework for Calibrating Individualized Therapeutic Indices in Cancer

The development and clinical implementation of evidence-based precision medicine strategies has become a realistic possibility, primarily due to the rapid accumulation of large-scale genomics and pharmacological data from diverse model systems: patients, cell-lines and drug perturbation studies. We introduce a novel Bayesian modeling framework called the individualized theRapeutic index (iRx) model to integrate high-throughput pharmacogenomic data across model systems. Our iRx model achieves three main goals: first, it exploits the conserved biology between patients and cell-lines to calibrate therapeutic response of drugs in patients; second, it finds optimal cell line avatars as proxies for patient(s); and finally, it identifies key genomic drivers explaining cell line-patient similarities. This is achieved through a semi-supervised learning approach, that conflates (unsupervised) sparse latent factor models with (supervised) penalized regression techniques. We propose a unified and tractable Bayesian model for estimation, and inference is conducted via efficient posterior sampling schemes. We illustrate and validate our approach using two existing clinical trial datasets in multiple myeloma and breast cancer studies. We show that our iRx model improves prediction accuracy compared to naive alternative approaches, and it consistently outperforms existing methods in literature in both in multiple simulation scenarios as well as real clinical examples.

genomics↗

bioRxiv2021

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗