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Abstract The ribonucleic acid (RNA) of the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is detectable in municipal wastewater as infected individuals can shed the virus in their feces. Viral concentration in wastewater can inform the severity of the COVID-19 pandemic but observations can be noisy and sparse and hence hamper the epidemiological interpretation. Motivated by a Canadian nationwide wastewater surveillance data set, unlike previous studies, we propose a novel Bayesian statistical framework based on the theories of functional data analysis to tackle the challenges embedded in the longitudinal wastewater monitoring data. By employing this framework to analyze the large-scale data set from the nationwide wastewater surveillance program covering 15 sampling sites across Canada, we successfully detect the true trends of viral concentration out of noisy and sparsely observed viral concentrations, and accurately forecast the future trajectory of viral concentrations in wastewater. Along with the excellent performance assessment using simulated data, this study shows that the proposed novel framework is a useful statistical tool and has a significant potential in supporting the epidemiological interpretation of noisy viral concentration measurements from wastewater samples in a real-life setting.

The real-time polymerase chain reaction (PCR), commonly known as quantitative PCR (qPCR), is increasingly common in environmental microbiology applications. During the COVID-19 pandemic, qPCR combined with reverse transcription (RT-qPCR) has been used to detect and quantify SARS-CoV-2 in clinical diagnoses and wastewater monitoring of local trends. Estimation of concentrations using qPCR often features a log-linear standard curve model calibrating quantification cycle (Cq) values obtained from underlying fluorescence measurements to standard concentrations. This process works well at high concentrations within a linear dynamic range but has diminishing reliability at low concentrations because it cannot explain “non-standard” data such as Cq values reflecting increasing variability at low concentrations or non-detects that do not yield Cq values at all. Here, fundamental probabilistic modeling concepts from classical quantitative microbiology were integrated into standard curve modeling approaches by reflecting well-understood mechanisms for random error in microbial data. This work showed that data diverging from the log-linear regression model at low concentrations as well as non-detects can be seamlessly integrated into enhanced standard curve analysis. The newly developed model provides improved representation of standard curve data at low concentrations while converging asymptotically upon conventional log-linear regression at high concentrations and adding no fitting parameters. Such modeling facilitates exploration of the effects of various random error mechanisms in experiments generating standard curve data, enables quantification of uncertainty in standard curve parameters, and is an important step toward quantifying uncertainty in qPCR-based concentration estimates. Improving understanding of the random error in qPCR data and standard curve modeling is especially important when low concentrations are of particular interest and inappropriate analysis can unduly affect interpretation, conclusions regarding lab performance, reported concentration estimates, and associated decision-making.

The investigation was executed with nine treatments viz. nano forms of ferrous sulfide (7, 14, 21, 28 ppm) and macro ferrous sulphate (0.2, 0.4, 0.6, 0.8 per cent) along with control, and were applied as foliar sprays after 30 days of transplanting on two varieties of calendula namely Fiesta Gitana Mix’ and ‘Fiesta Yellow’ during 2018 and 2019. The experiment was laid out in factorial randomized block design with three replications. Application of 0.8 % FeSO4 recorded maximum number of branches (26.75), plant height (29.73 cm), plant spread (45.17 cm), number of leaves (22.63) and seed test weight (15.63 g) and number of flowers per plant (134.04). However, application of 0.2% macro FeSO4 resulted in early bud appearance (50.50 days) and higher flower diameter (8.09 cm). ‘Fiesta Gitana Mix’ outperformed over ‘Fiesta Yellow’ for most of the vegetative and floral characters. The ‘Fiesta Yellow’ variety with oil content (13.97%) had an edge over ‘Fiesta Gitana Mix’.

The COVID-19 pandemic has stimulated wastewater-based surveillance, allowing public health to track the epidemic by monitoring the concentration of the genetic fingerprints of SARS-CoV-2 shed in wastewater by infected individuals. Wastewater-based surveillance for COVID-19 is still in its infancy. In particular, the quantitative link between clinical cases observed through traditional surveillance and the signals from viral concentrations in wastewater is still developing and hampers interpretation of the data and actionable public-health decisions. We present a modelling framework that includes both SARS-CoV-2 transmission at the population level and the fate of SARS-CoV-2 RNA particles in the sewage system after faecal shedding by infected persons in the population. Using our mechanistic representation of the combined clinical/wastewater system, we perform exploratory simulations to quantify the effect of surveillance effectiveness, public-health interventions and vaccination on the discordance between clinical and wastewater signals. We also apply our model to surveillance data from three Canadian cities to provide wastewater-informed estimates for the actual prevalence, the effective reproduction number and incidence forecasts. We find that wastewater-based surveillance, paired with this model, can complement clinical surveillance by supporting the estimation of key epidemiological metrics and hence better triangulate the state of an epidemic using this alternative data source.

Farriery is a critical component of healthcare services for working equids. However, in India, an informal workforce, lack of structured training facilities and non-implementation of farriery regulations pose challenges for quality farriery. Brooke India, an equine welfare organisation, has undertaken many initiatives aiming to improve farriery services, including technical training and engagement with equid-owning communities. However, this has met with varying success. The study aimed to identify factors that prevent farriers providing quality farriery services. Focus-group discussions were conducted with farriers from two districts of Uttar Pradesh with varying programme outcomes. Within each area, farriers were grouped according to previous level of engagement with Brooke programmes. Demand for services, farrier status, the external environment and technical training and knowledge were identified as key elements that affected farriery work. These factors were very context specific: in areas where brick kilns provided the majority of customers, recent closures had resulted in an increase in those farriers’ feeling of insecurity. A systems approach to improving farriery services, taking these factors into account, is advised. Mentoring-based capacity building, which is closely aligned to farrier needs and expectations, is expected to have positive results in terms of technical skill and farrier engagement.

ABSTRACT Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo. To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli. Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms. IMPORTANCE With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress.

While small molecule inhibitors of the bacterial ribosome have been instrumental in understanding protein translation, no such probes exist to study ribosome biogenesis. We screened a diverse chemical collection that included previously approved drugs for compounds that induced cold sensitive growth inhibition in the model bacterium Escherichia coli. Among the most cold sensitive was lamotrigine, an anticonvulsant drug. Lamotrigine treatment resulted in the rapid accumulation of immature 30S and 50S ribosomal subunits at 15°C. Importantly, this was not the result of translation inhibition, as lamotrigine was incapable of perturbing protein synthesis in vivo or in vitro. Spontaneous suppressor mutations blocking lamotrigine activity mapped solely to the poorly characterized domain II of translation initiation factor IF2 and prevented the binding of lamotrigine to IF2 in vitro. This work establishes lamotrigine as a widely available chemical probe of bacterial ribosome biogenesis and suggests a role for E. coli IF2 in ribosome assembly.

Background With many global jurisdictions, Toronto, Canada, experienced an mpox outbreak in spring/summer 2022. Cases declined following implementation of a large vaccination campaign. A surge in early 2023 led to speculation that asymptomatic and/or undetected local transmission was occurring in the city. Methods Mpox cases and positive laboratory results are reported to Toronto Public Health. Epidemic curves and descriptive risk factor summaries for the 2022 and 2023 outbreaks were generated. First- and second-dose vaccination was monitored. Mpox virus wastewater surveillance and whole genome sequencing were conducted to generate hypotheses about the source of the 2023 resurgence. Results An overall 515 cases were reported in spring/summer 2022 and 17 in the 2022–2023 resurgence. Wastewater data correlated with the timing of cases. Whole genome sequencing showed that 2022–2023 cases were distinct from 2022 cases and closer to sequences from another country, suggesting a new importation as a source. At the start of the resurgence, approximately 16% of first-dose vaccine recipients had completed their second dose. Conclusions This investigation demonstrates the importance of ongoing surveillance and preparedness for mpox outbreaks. Undetected local transmission was not a likely source of the 2022–2023 resurgence. Ongoing preexposure vaccine promotion remains important to mitigate disease burden. [ABSTRACT FROM AUTHOR]