Wastewater Sequencing Reveals Community and Variant Dynamics of the Collective Human Virome

Wastewater is a discarded human by-product, but its analysis may help us understand the health of populations. Epidemiologists first analyzed wastewater to track outbreaks of poliovirus decades ago, but so-called wastewater-based epidemiology was reinvigorated to monitor SARS-CoV-2 levels while bypassing the difficulties and pit falls of individual testing. Current approaches overlook the activity of most human viruses and preclude a deeper understanding of human virome community dynamics. Here, we conduct a comprehensive sequencing-based analysis of 363 longitudinal wastewater samples from ten distinct sites in two major cities. Critical to detection is the use of a viral probe capture set targeting thousands of viral species or variants. Over 450 distinct pathogenic viruses from 28 viral families are observed, most of which have never been detected in such samples. Sequencing reads of established pathogens and emerging viruses correlate to clinical data sets of SARS-CoV-2, influenza virus, and monkeypox viruses, outlining the public health utility of this approach. Viral communities are tightly organized by space and time. Finally, the most abundant human viruses yield sequence variant information consistent with regional spread and evolution. We reveal the viral landscape of human wastewater and its potential to improve our understanding of outbreaks, transmission, and its effects on overall population health

Local modal regression

A local modal estimation procedure is proposed for the regression function in a nonparametric regression model. A distinguishing characteristic of the proposed procedure is that it introduces an additional tuning parameter that is automatically selected using the observed data in order to achieve both robustness and efficiency of the resulting estimate. We demonstrate both theoretically and empirically that the resulting estimator is more efficient than the ordinary local polynomial regression estimator in the presence of outliers or heavy tail error distribution (such as t-distribution). Furthermore, we show that the proposed procedure is as asymptotically efficient as the local polynomial regression estimator when there are no outliers and the error distribution is a Gaussian distribution. We propose an EM type algorithm for the proposed estimation procedure. A Monte Carlo simulation study is conducted to examine the finite sample performance of the proposed method. The simulation results confirm the theoretical findings. The proposed methodology is further illustrated via an analysis of a real data example

Precipitation before Flowering Determined Effectiveness of Leaf Removal Timing and Irrigation on Wine Composition of Merlot Grapevine

Grapevine productivity, and berry and wine flavonoid concentration, depend on the interactions of cultivar, environment, and applied cultural practices. We characterized the effects that mechanical leaf removal and irrigation treatments had on the flavonoid concentration of ‘Merlot’ (Vitis vinifera, L.) grape berries and wines in a hot climate over two growing seasons with contrasting precipitation patterns. Leaves were removed by machine, either at prebloom (PBLR), or at post-fruit-set (PFLR), or not removed (control) and irrigation was either applied as sustained deficit irrigation (SDI) at 0.8 of crop evapotranspiration (ETc) from budbreak to fruit set, or regulated deficit irrigation (RDI) at 0.8 ETc from bud break to fruit set, 0.5 ETc from fruit set to veraison, and 0.8 ETc from veraison to harvest, of ETc In 2014, PFLR reduced the leaf area index (LAI) compared to control. The RDI decreased season-long leaf water potential (ΨInt) compared to SDI. However, in 2015, none of the treatments affected LAI or ΨInt. In 2014, berry flavonoid concentrations were reduced by PBLR as well as SDI. SDI increased the flavonoid concentrations in wine, and PFLR increased some wine flavonols in one season. No factor affected the concentrations of wine proanthocyanidins or mean degree of polymerization. Thus, mechanical PFLR and RDI may increase berry flavonoid accumulation without yield reduction, in red wine grapes cultivars grown in hot climates when precipitation after bud break is lacking. However, spring precipitation may influence the effectiveness of these practices as evidenced by this work in a changing climate