Wastewater based surveillance can be used to reduce clinical testing intensity on a university campus.

Clinical testing has been a vital part of the response to and suppression of the COVID-19 pandemic; however, testing imposes significant burdens on a population. College students had to contend with clinical testing while simultaneously dealing with health risks and the academic pressures brought on by quarantines, changes to virtual platforms, and other disruptions to daily life. The objective of this study was to analyze whether wastewater surveillance can be used to decrease the intensity of clinical testing while maintaining reliable measurements of diseases incidence on campus.

Expanding a Wastewater-Based Surveillance Methodology for DNA Isolation from a Workflow Optimized for SARS-CoV-2 RNA Quantification.

Wastewater-based surveillance (WBS) is a noninvasive, epidemiological strategy for assessing the spread of COVID-19 in communities. This strategy was based upon wastewater RNA measurements of the viral target, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The utility of WBS for assessing the spread of COVID-19 has motivated research to measure targets beyond SARS-CoV-2, including pathogens containing DNA.

Transcriptome analysis in a humanized mouse model of familial dysautonomia reveals tissue-specific gene expression disruption in the peripheral nervous system.

Familial dysautonomia (FD) is a rare recessive neurodevelopmental disease caused by a splice mutation in the Elongator acetyltransferase complex subunit 1 (ELP1) gene. This mutation results in a tissue-specific reduction of ELP1 protein, with the lowest levels in the central and peripheral nervous systems (CNS and PNS, respectively). FD patients exhibit complex neurological phenotypes due to the loss of sensory and autonomic neurons.

Parallelized engineering of mutational models using piggyBac transposon delivery of CRISPR libraries.

New technologies and large-cohort studies have enabled novel variant discovery and association at unprecedented scale, yet functional characterization of these variants remains paramount to deciphering disease mechanisms. Approaches that facilitate parallelized genome editing of cells of interest or induced pluripotent stem cells (iPSCs) have become critical tools toward this goal. Here, we developed an approach that incorporates libraries of CRISPR-Cas9 guide RNAs (gRNAs) together with inducible Cas9 into a piggyBac (PB) transposon system to engineer dozens to hundreds of genomic variants in parallel against isogenic cellular backgrounds.

Transcriptome analysis in a humanized mouse model of familial dysautonomia reveals tissue-specific gene expression disruption in the peripheral nervous system.

Familial dysautonomia (FD) is a rare recessive neurodevelopmental disease caused by a splice mutation in the Elongator acetyltransferase complex subunit 1 ( ) gene. This mutation results in a tissue-specific reduction of ELP1 protein, with the lowest levels in the central and peripheral nervous systems (CNS and PNS, respectively). FD patients exhibit complex neurological phenotypes due to the loss of sensory and autonomic neurons.

Comparison of Electronegative Filtration to Magnetic Bead-Based Concentration and V2G-qPCR to RT-qPCR for Quantifying Viral SARS-CoV-2 RNA from Wastewater.

Methods of wastewater concentration (electronegative filtration (ENF) versus magnetic bead-based concentration (MBC)) were compared for the analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), beta-2 microglobulin, and human-coronavirus OC43. Using ENF as the concentration method, two quantitative Polymerase Chain Reaction (qPCR) analytical methods were also compared: Volcano 2 Generation (V2G)-qPCR and reverse transcriptase (RT)-qPCR measuring three different targets of the virus responsible for the COVID-19 illness (N1, modified N3, and ORF1ab). Correlations between concentration methods were strong and statistically significant for SARS-CoV-2 (r=0.

Geospatially-resolved public-health surveillance via wastewater sequencing.

Wastewater, which contains everything from pathogens to pollutants, is a geospatially-and temporally-linked microbial fingerprint of a given population. As a result, it can be leveraged for monitoring multiple dimensions of public health across locales and time. Here, we integrate targeted and bulk RNA sequencing (n=1,419 samples) to track the viral, bacterial, and functional content over geospatially distinct areas within Miami Dade County from 2020-2022.

Relationships between SARS-CoV-2 in Wastewater and COVID-19 Clinical Cases and Hospitalizations, with and without Normalization against Indicators of Human Waste.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant.

Tissue- and cell-type-specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models.

Chromosome 16p11.2 reciprocal genomic disorder, resulting from recurrent copy-number variants (CNVs), involves intellectual disability, autism spectrum disorder (ASD), and schizophrenia, but the responsible mechanisms are not known. To systemically dissect molecular effects, we performed transcriptome profiling of 350 libraries from six tissues (cortex, cerebellum, striatum, liver, brown fat, and white fat) in mouse models harboring CNVs of the syntenic 7qF3 region, as well as cellular, transcriptional, and single-cell analyses in 54 isogenic neural stem cell, induced neuron, and cerebral organoid models of CRISPR-engineered 16p11.

A Rapid, Isothermal, and Point-of-Care System for COVID-19 Diagnostics.

The COVID-19 pandemic has had a profound, detrimental effect on economies and societies worldwide. Where the pandemic has been controlled, extremely high rates of diagnostic testing for the SARS-CoV-2 virus have proven critical, enabling isolation of cases and contact tracing. Recently, diagnostic testing has been supplemented with wastewater measures to evaluate the degree to which communities have infections.

Dystonia-specific mutations in THAP1 alter transcription of genes associated with neurodevelopment and myelin.

Dystonia is a neurologic disorder associated with an increasingly large number of genetic variants in many genes, resulting in characteristic disturbances in volitional movement. Dissecting the relationships between these mutations and their functional outcomes is critical in understanding the pathways that drive dystonia pathogenesis. Here we established a pipeline for characterizing an allelic series of dystonia-specific mutations.

TAF1 Transcripts and Neurofilament Light Chain as Biomarkers for X-linked Dystonia-Parkinsonism.

Background: X-linked dystonia-parkinsonism is a rare neurological disease endemic to the Philippines. Dystonic symptoms appear in males at the mean age of 40 years and progress to parkinsonism with degenerative pathology in the striatum. A retrotransposon inserted in intron 32 of the TAF1 gene leads to alternative splicing in the region and a reduction of the full-length mRNA transcript.

Kctd13-deficient mice display short-term memory impairment and sex-dependent genetic interactions.

The 16p11.2 BP4-BP5 deletion and duplication syndromes are associated with a complex spectrum of neurodevelopmental phenotypes that includes developmental delay and autism spectrum disorder, with a reciprocal effect on head circumference, brain structure and body mass index. Mouse models of the 16p11.

Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder.

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD.

Next Generation Sequencing of Prenatal Structural Chromosomal Rearrangements Using Large-Insert Libraries.

Precise tests for genomic structural variation (SV) are essential for accurate diagnosis of prenatal genome abnormalities. The two most ubiquitous traditional methods for prenatal SV assessment, karyotyping and chromosomal microarrays, do not provide sufficient resolution for some clinically actionable SVs. Standard whole-genome sequencing (WGS) overcomes shortcomings of traditional techniques by providing base-pair resolution of the entire accessible genome.

Loss of LDAH associated with prostate cancer and hearing loss.

Great strides in gene discovery have been made using a multitude of methods to associate phenotypes with genetic variants, but there still remains a substantial gap between observed symptoms and identified genetic defects. Herein, we use the convergence of various genetic and genomic techniques to investigate the underpinnings of a constellation of phenotypes that include prostate cancer (PCa) and sensorineural hearing loss (SNHL) in a human subject. Through interrogation of the subject's de novo, germline, balanced chromosomal translocation, we first identify a correlation between his disorders and a poorly annotated gene known as lipid droplet associated hydrolase (LDAH).

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder.

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories.