Biology subjects

Schaffert, S.

Publications and source records attributed to Schaffert, S..

3 recordsLinked to original sources

bioRxiv2021

Identification and targeting of a pan-genotypic influenza A virus RNA structure that mediates packaging and disease.

Currently approved anti-influenza drugs target viral proteins, are subtype limited, and are challenged by rising antiviral resistance. To overcome these limitations, we sought to identify a conserved essential RNA secondary structure within the genomic RNA predicted to have greater constraints on mutation in response to therapeutics targeting this structure. Here, we identified and genetically validated an RNA stemloop structure we termed PSL2, which serves as a packaging signal for genome segment PB2 and is highly conserved across influenza A virus (IAV) isolates. RNA structural modeling rationalized known packaging-defective mutations and allowed for predictive mutagenesis tests. Disrupting and compensating mutations of PSL2s structure give striking attenuation and restoration, respectively, of in vitro virus packaging and mortality in mice. Antisense Locked Nucleic Acid oligonucleotides (LNAs) designed against PSL2 dramatically inhibit IAV in vitro against viruses of different strains and subtypes, possess a high barrier to the development of antiviral resistance, and are equally effective against oseltamivir carboxylate-resistant virus. A single dose of LNA administered 3 days after, or 14 days before, a lethal IAV inoculum provides 100% survival. Moreover, such treatment led to the development of strong immunity to rechallenge with a ten-fold lethal inoculum. Together, these results have exciting implications for the development of a versatile novel class of antiviral therapeutics capable of prophylaxis, post-exposure treatment, and "just-in-time" universal vaccination against all IAV strains, including drug-resistant pandemics. One Sentence SummaryTargeting a newly identified conserved RNA structure in the packaging signal region of influenza segment PB2 abrogates virus production in vitro and dramatically attenuates disease in vivo.

microbiology↗

bioRxiv2021

Proximal and Distal Nephron-specific Adaptation to Furosemide

Furosemide, a widely prescribed diuretic for edema-forming states, inhibits sodium reabsorption in the thick ascending limb of the nephron. Tubular adaptation to diuretics has been observed, but the range of mechanisms along the nephron has not been fully explored. Using morphometry, we show that furosemide induces renal tubular epithelial hyperplasia selectively in distal nephron segments. By comparison, we find progressive cellular hypertrophy in proximal and distal nephron segments. We next utilize single cell RNA sequencing of vehicle- and furosemide-treated mice to define potential mechanisms of diuretic resistance. Consistent with distal tubular cell hyperplasia, we detect a net increase in DCT cell number and Birc5, an anti-apoptotic and pro-growth gene, in a subset of DCT cells, as the most prominently up-regulated gene across the nephron. We also map a gradient of cell-specific transcriptional changes congruent with enhanced distal sodium transport. Furosemide stimulates expression of the mitogen IGF-1. Thus, we developed a mouse model of inducible deletion of renal tubular IGF-1 receptor and show reduced kidney growth and proximal, but not distal, tubular hypertrophy by furosemide. Moreover, genes that promote enhanced bioavailability of IGF-1 including Igfbp1 and Igfbp5 are significantly and differentially expressed in proximal tubular segments and correspond to IGF-1R-dependent hypertrophy. In contrast, downstream PI3-kinase signaling genes including Pdk1, Akt1, Foxo3, FKBP4, Eif2BP4, and Spp1 are significantly and differentially expressed in distal nephron segments and correspond to IGF-1R-independent hypertrophy. These findings highlight novel mechanisms of tubular remodeling and diuretic resistance, provide a repository of transcriptional responses to a common drug, and expand the implications of long-term loop diuretic use for human disease.

physiology↗

bioRxiv2017

Leveraging heterogeneity across multiple data sets increases accuracy of cell-mixture deconvolution and reduces biological and technical biases

In silico quantification of cell proportions from mixed-cell transcriptomics data (deconvolution) requires a reference expression matrix, called basis matrix. We hypothesized that matrices created using only healthy samples from a single microarray platform would introduce biological and technical biases in deconvolution. We show presence of such biases in two existing matrices, IRIS and LM22, irrespective of the deconvolution method used. Here, we present immunoStates, a basis matrix built using 6160 samples with different disease states across 42 microarray platforms. We found that immunoStates significantly reduced biological and technical biases. We further show that cellular proportion estimates using immunoStates are consistently more correlated with measured proportions than IRIS and LM22, across all methods. Importantly, we found that different methods have virtually no effect once the basis matrix is chosen. Our results demonstrate the need and importance of incorporating biological and technical heterogeneity in a basis matrix for achieving consistently high accuracy.

bioinformatics↗