A long-term growth stable Halomonas sp. deleted with multiple transposases guided by its metabolic network model Halo-ecGEM.

Microbial instability is a common problem during bio-production based on microbial hosts. Halomonas bluephagenesis has been developed as a chassis for next generation industrial biotechnology (NGIB) under open and unsterile conditions. However, the hidden genomic information and peculiar metabolism have significantly hampered its deep exploitation for cell-factory engineering. Based on the freshly completed genome sequence of H. bluephagenesis TD01, which reveals 1889 biological process-associated genes grouped into 84 GO-slim terms. An enzyme constrained genome-scale metabolic model Halo-ecGEM was constructed, which showed strong ability to simulate fed-batch fermentations. A visible salt-stress responsive landscape was achieved by combining GO-slim term enrichment and CVT-based omics profiling, demonstrating that cells deploy most of the protein resources by force to support the essential activity of translation and protein metabolism when exposed to salt stress. Under the guidance of Halo-ecGEM, eight transposases were deleted, leading to a significantly enhanced stability for its growth and bioproduction of various polyhydroxyalkanoates (PHA) including 3-hydroxybutyrate (3HB) homopolymer PHB, 3HB and 3-hydroxyvalerate (3HV) copolymer PHBV, as well as 3HB and 4-hydroxyvalerate (4HB) copolymer P34HB. This study sheds new light on the metabolic characteristics and stress-response landscape of H. bluephagenesis, achieving for the first time to construct a long-term growth stable chassis for industrial applications. For the first time, it was demonstrated that genome encoded transposons are the reason for microbial instability during growth in flasks and fermentors.

OsPRMT6a-mediated arginine methylation of OsJAZ1 regulates jasmonate signaling and spikelet development in rice.

Although both protein arginine methylation (PRMT) and jasmonate (JA) signaling are crucial for regulating plant development, the relationship between these processes in the control of spikelet development remains unclear. In this study, we used the CRISPR/Cas9 technology to generate two OsPRMT6a loss-of-function mutants that exhibit various abnormal spikelet structures. Interestingly, we found that OsPRMT6a can methylate arginine residues in JA signal repressors OsJAZ1 and OsJAZ7. We showed that arginine methylation of OsJAZ1 enhances the binding affinity of OsJAZ1 with the JA receptors OsCOI1a and OsCOI1b in the presence of JAs, thereby promoting the ubiquitination of OsJAZ1 by the SCFOsCOI1a/OsCOI1b complex and degradation via the 26S proteasome. This process ultimately releases OsMYC2, a core transcriptional regulator in the JA signaling pathway, to activate or repress JA-responsive genes, thereby maintaining normal plant (spikelet) development. However, in the osprmt6a-1 mutant, reduced arginine methylation of OsJAZ1 impaires the interaction between OsJAZ1 and OsCOI1a/OsCOI1b in the presence of JAs. As a result, OsJAZ1 proteins become more stable, repressing JA responses, thus causing the formation of abnormal spikelet structures. Moreover, we discovered that JA signaling reduces the OsPRMT6a mRNA level in an OsMYC2-dependent manner, thereby establishing a negative feedback loop to balance JA signaling. We further found that OsPRMT6a-mediated arginine methylation of OsJAZ1 likely serves as a switch to tune JA signaling to maintain normal spikelet development under harsh environmental conditions such as high temperatures. Collectively, our study establishes a direct molecular link between arginine methylation and JA signaling in rice.

Association of Nightly Fasting, Meal Frequency, and Skipping Meals with Metabolic Syndrome among Kuwaiti Adults.

Mounting evidence suggests that meal timing and frequency are associated with cardiometabolic health by influencing circadian rhythms. However, the evidence is inconsistent and limited, especially in non-Western cultures. This cross-sectional study aims to investigate the association between temporal habits of dietary intake, such as nightly fasting duration and meal frequency, and metabolic syndrome among Kuwaiti adults. A 24-hour recall was used to assess temporal habits of dietary intake. Meal frequency was defined as the number of daily eating episodes. The study included a total of 757 adults aged 20 years and older. The participants' mean age was 37.8 ± 12.3 years. After adjusting for all confounders, higher meal frequency was found to be associated with a lower prevalence of metabolic syndrome in adults (OR, 0.43; 95%CI, 0.19-0.96) and a lower prevalence of elevated triglycerides in men only (OR, 0.23; 95%CI, 0.09-0.60). No association was found between nightly fasting and metabolic syndrome, but a longer fasting duration was associated with a lower prevalence of elevated triglycerides (OR, 0.19; 95%CI, 0.06-0.63). The findings suggest that having frequent meals and longer durations of nightly fasting may help decrease the risk of metabolic syndrome and elevated triglycerides.

Eye infection risks from Pseudomonas aeruginosa via hand soap and eye drops.

Eye infections from bacterial contamination of bulk-refillable liquid soap dispensers and artificial tear eye drops continue to occur, resulting in adverse health outcomes that include impaired vision or eye enucleation. Pseudomonas aeruginosa (P. aeruginosa), a common cause of eye infections, can grow in eye drop containers and refillable soap dispensers to high numbers. To assess the risk of eye infection, a quantitative microbial risk assessment for P. aeruginosa was conducted to predict the probability of an eye infection for two potential exposure scenarios: (i) individuals using bacteria-contaminated eye drops and (ii) contact lens wearers washing their hands with bacteria-contaminated liquid soap prior to placing the lens. The median risk of an eye infection using contaminated eye drops and hand soap for both single and multiple exposure events (per day) ranged from 10-1 to 10-4, with contaminated eye drops having the greater risk. The concentration of P. aeruginosa was identified as the parameter contributing the greatest variance on eye infection risk; therefore, the prevalence and level of bacterial contamination of the product would have the greatest influence on health risk. Using eye drops in a single-use container or with preservatives can mitigate bacterial growth, and using non-refillable soap dispensers is recommended to reduce contamination of hand soap. Given the opportunistic nature of P. aeruginosa and its ability to thrive in unique environments, additional safeguards to mitigate bacterial growth and exposure are warranted.IMPORTANCEPseudomonas aeruginosa (P. aeruginosa) is a pathogen that can persist in a variety of unusual environments and continues to pose a significant risk for public health. This quantitative microbial risk assessment (QMRA) estimates the potential human health risks, specifically for eye infections, associated with exposure to P. aeruginosa in bacteria-contaminated artificial tear eye drops and hand soap. This study applies the risk assessment framework of QMRA to evaluate eye infection risks through both consumer products. The study examines the prevalence of this pathogen in eye drops and soap, as well as the critical need to implement measures that will mitigate bacterial exposure (e.g., single-use soap dispensers and eye drops with preservatives). Additionally, limitations and challenges are discussed, including the need to incorporate data regarding consumer practices, which may improve exposure assessments and health risk estimates.

Low-level resource partitioning supports coexistence among functionally redundant bacteria during successional dynamics.

Members of microbial communities can substantially overlap in substrate use. However, what enables functionally redundant microorganisms to coassemble or even stably coexist remains poorly understood. Here, we show that during unstable successional dynamics on complex, natural organic matter, functionally redundant bacteria can coexist by partitioning low-concentration substrates even though they compete for one simple, dominant substrate. We allowed ocean microbial communities to self-assemble on leachates of the brown seaweed Fucus vesiculosus and then analyzed the competition among 10 taxonomically diverse isolates representing two distinct stages of the succession. All, but two isolates, exhibited an average of 90% ± 6% pairwise overlap in resource use, and functional redundancy of isolates from the same assembly stage was higher than that from between assembly stages, leading us to construct a simpler four-isolate community with two isolates from each of the early and late stages. We found that, although the short-term dynamics of the four-isolate communities in F. vesiculosus leachate was dependent on initial isolate ratios, in the long term, the four isolates stably coexist in F. vesiculosus leachate, albeit with some strains at low abundance. We therefore explored the potential for nonredundant substrate use by genomic content analysis and RNA expression patterns. This analysis revealed that the four isolates mainly differed in peripheral metabolic pathways, such as the ability to degrade pyrimidine, leucine, and tyrosine, as well as aromatic substrates. These results highlight the importance of fine-scale differences in metabolic strategies for supporting the frequently observed coexistence of large numbers of rare organisms in natural microbiomes.

Assessment of a SARS-CoV-2 wastewater monitoring program in El Paso, Texas, from November 2020 to June 2022.

The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4-24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso.

Flux optimization using multiple promoters in Halomonas bluephagenesis as a model chassis of the next generation industrial biotechnology.

Predictability and robustness are challenges for bioproduction because of the unstable intracellular synthetic activities. With the deeper understanding of the gene expression process, fine-tuning has become a meaningful tool for biosynthesis optimization. This study characterized several gene expression elements and constructed a multiple inducible system that responds to ten different small chemical inducers in halophile bacterium Halomonas bluephagenesis. Genome insertion of regulators was conducted for the purpose of gene cluster stabilization and regulatory plasmid simplification. Additionally, dynamic ranges of the multiple inducible systems were tuned by promoter sequence mutations to achieve diverse scopes for high-resolution gene expression control. The multiple inducible system was successfully employed to precisely control chromoprotein expression, lycopene and poly-3-hydroxybutyrate (PHB) biosynthesis, resulting in colorful bacterial pictures, optimized cell growth, lycopene and PHB accumulation. This study demonstrates a desirable approach for fine-tuning of rational and efficient gene expressions, displaying the significance for metabolic pathway optimization.

Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study.

Background: Tracking infectious diseases at the community level is challenging due to asymptomatic infections and the logistical complexities of mass surveillance. Wastewater surveillance has emerged as a valuable tool for monitoring infectious disease agents including SARS-CoV-2 and Mpox virus. However, detecting the Mpox virus in wastewater is particularly challenging due to its relatively low prevalence in the community. In this study, we aim to characterize three molecular assays for detecting and tracking the Mpox virus in wastewater from El Paso, Texas, during February and March 2023. Methods: In this study, a combined approach utilizing three real-time PCR assays targeting the C22L, F3L, and F8L genes and sequencing was employed to detect and track the Mpox virus in wastewater samples. The samples were collected from four sewersheds in the City of El Paso, Texas, during February and March 2023. Wastewater data was compared with reported clinical case data in the city. Findings: Mpox virus DNA was detected in wastewater from all the four sewersheds, whereas only one Mpox case was reported during the sampling period. Positive signals were still observed in multiple sewersheds after the Mpox case was identified. Higher viral concentrations were found in the pellet than in the supernatant of wastewater. Notably, an increasing trend in viral concentration was observed approximately 1-2 weeks before the reporting of the Mpox case. Further sequencing and epidemiological analysis provided supporting evidence for unreported Mpox infections in the city. Interpretation: Our analysis suggests that the Mpox cases in the community is underestimated. The findings emphasize the value of wastewater surveillance as a public health tool for monitoring infectious diseases even in low-prevalence areas, and the need for heightened vigilance to mitigate the spread of Mpox disease for safeguarding global health. Funding: Center of Infectious Diseases at UTHealth, the University of Texas System, and the Texas Epidemic Public Health Institute. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of these funding organizations.

Recent Advances on the Molecular Mechanism and Clinical Trials of Venous Thromboembolism.

Venous thromboembolism is a condition that includes deep vein thrombosis and pulmonary embolism. It is the third most common cardiovascular disease behind acute coronary heart disease and stroke. Over the past few years, growing research suggests that venous thrombosis is also related to the immune system and inflammatory factors have been confirmed to be involved in venous thrombosis. The role of inflammation and inflammation-related biomarkers in cerebrovascular thrombotic disease is the subject of ongoing debate. P-selectin leads to platelet-monocyte aggregation and stimulates vascular inflammation and thrombosis. The dysregulation of miRNAs has also been reported in venous thrombosis, suggesting the involvement of miRNAs in the progression of venous thrombosis. Plasminogen activator inhibitor-1 (PAI-1) is a crucial component of the plasminogen-plasmin system, and elevated levels of PAI-1 in conjunction with advanced age are significant risk factors for thrombosis. In addition, it has been showed that one of the ways that neutrophils promote venous thrombosis is the formation of neutrophil extracellular traps (NETs). In recent years, the role of extracellular vesicles (EVs) in the occurrence and development of VTE has been continuously revealed. With the advancement of research technology, the complex regulatory role of EVs on the coagulation process has been gradually discovered. However, our understanding of the causes and consequences of these changes in venous thrombosis is still limited. Therefore, we review our current understanding the molecular mechanisms of venous thrombosis and the related clinical trials, which is crucial for the future treatment of venous thrombosis.

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.

Engineering low-salt growth Halomonas Bluephagenesis for cost-effective bioproduction combined with adaptive evolution.

Halophilic Halomonas bluephagenesis has been engineered to produce various added-value bio-compounds with reduced costs. However, the salt-stress regulatory mechanism remained unclear. H. bluephagenesis was randomly mutated to obtain low-salt growing mutants via atmospheric and room temperature plasma (ARTP). The resulted H. bluephagenesis TDH4A1B5 was constructed with the chromosomal integration of polyhydroxyalkanoates (PHA) synthesis operon phaCAB and deletion of phaP1 gene encoding PHA synthesis associated protein phasin, forming H. bluephagenesis TDH4A1B5P, which led to increased production of poly(3-hydroxybutyrate) (PHB) and poly(3-hydroxybutyrate-co-4-hydrobutyrate) (P34HB) by over 1.4-fold. H. bluephagenesis TDH4A1B5P also enhanced production of ectoine and threonine by 50% and 77%, respectively. A total 101 genes related to salinity tolerance was identified and verified via comparative genomic analysis among four ARTP mutated H. bluephagenesis strains. Recombinant H. bluephagenesis TDH4A1B5P was further engineered for PHA production utilizing sodium acetate or gluconate as sole carbon source. Over 33% cost reduction of PHA production could be achieved using recombinant H. bluephagenesis TDH4A1B5P. This study successfully developed a low-salt tolerant chassis H. bluephagenesis TDH4A1B5P and revealed salt-stress related genes of halophilic host strains.

Making waves: Integrating wastewater surveillance with dynamic modeling to track and predict viral outbreaks.

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and applicability of dynamic models. The integration of wastewater surveillance data with dynamic models can enhance real-time tracking and prevalence estimation, forecast viral transmission and intervention effectiveness, and most importantly, provide a mechanistic understanding of infectious disease dynamics and the driving factors. Dynamic modeling of wastewater surveillance data will advance the development of a predictive and responsive monitoring system to improve pandemic preparedness and population health.

Prolonged viral shedding from noninfectious individuals confounds wastewater-based epidemiology.

Wastewater surveillance has been widely used to track and estimate SARS-CoV-2 incidence. While both infectious and recovered individuals shed virus into wastewater, epidemiological inferences using wastewater often only consider the viral contribution from the former group. Yet, the persistent shedding in the latter group could confound wastewater-based epidemiological inference, especially during the late stage of an outbreak when the recovered population outnumbers the infectious population. To determine the impact of recovered individuals' viral shedding on the utility of wastewater surveillance, we develop a quantitative framework that incorporates population-level viral shedding dynamics, measured viral RNA in wastewater, and an epidemic dynamic model. We find that the viral shedding from the recovered population can become higher than the infectious population after the transmission peak, which leads to a decrease in the correlation between wastewater viral RNA and case report data. Furthermore, the inclusion of recovered individuals' viral shedding into the model predicts earlier transmission dynamics and slower decreasing trends in wastewater viral RNA. The prolonged viral shedding also induces a potential delay in the detection of new variants due to the time needed to generate enough new cases for a significant viral signal in an environment dominated by virus shed by the recovered population. This effect is most prominent toward the end of an outbreak and is greatly affected by both the recovered individuals' shedding rate and shedding duration. Our results suggest that the inclusion of viral shedding from non-infectious recovered individuals into wastewater surveillance research is important for precision epidemiology.

3-Hydroxybutyrate ameliorates insulin resistance by inhibiting PPARγ Ser273 phosphorylation in type 2 diabetic mice.

3-Hydroxybutyrate (3HB) is a small ketone body molecule produced endogenously by the body in the liver. Previous studies have shown that 3HB can reduce blood glucose level in type 2 diabetic (T2D) patients. However, there is no systematic study and clear mechanism to evaluate and explain the hypoglycemic effect of 3HB. Here we demonstrate that 3HB reduces fasting blood glucose level, improves glucose tolerance, and ameliorates insulin resistance in type 2 diabetic mice through hydroxycarboxylic acid receptor 2 (HCAR2). Mechanistically, 3HB increases intracellular calcium ion (Ca2+) levels by activating HCAR2, thereby stimulating adenylate cyclase (AC) to increase cyclic adenosine monophosphate (cAMP) concentration, and then activating protein kinase A (PKA). Activated PKA inhibits Raf1 proto-oncogene serine/threonine-protein kinase (Raf1) activity, resulting in a decrease in extracellular signal-regulated kinases 1/2 (ERK1/2) activity and ultimately inhibiting peroxisome proliferator-activated receptor γ (PPARγ) Ser273 phosphorylation in adipocytes. Inhibition of PPARγ Ser273 phosphorylation by 3HB altered the expression of PPARγ regulated genes and reduced insulin resistance. Collectively, 3HB ameliorates insulin resistance in type 2 diabetic mice through a pathway of HCAR2/Ca2+/cAMP/PKA/Raf1/ERK1/2/PPARγ.

Wastewater pandemic preparedness: Toward an end-to-end pathogen monitoring program.

Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, molecular sciences, temporal-geospatial analytics, epidemiology and medical, and governmental and public health messaging, all of which present their own caveats. Here, we outline a framework for an integrated, state-wide, end-to-end human pathogen monitoring program using wastewater to track viral PPPs.

The emergence of a virus variant: dynamics of a competition model with cross-immunity time-delay validated by wastewater surveillance data for COVID-19.

We consider the dynamics of a virus spreading through a population that produces a mutant strain with the ability to infect individuals that were infected with the established strain. Temporary cross-immunity is included using a time delay, but is found to be a harmless delay. We provide some sufficient conditions that guarantee local and global asymptotic stability of the disease-free equilibrium and the two boundary equilibria when the two strains outcompete one another. It is shown that, due to the immune evasion of the emerging strain, the reproduction number of the emerging strain must be significantly lower than that of the established strain for the local stability of the established-strain-only boundary equilibrium. To analyze the unique coexistence equilibrium we apply a quasi steady-state argument to reduce the full model to a two-dimensional one that exhibits a global asymptotically stable established-strain-only equilibrium or global asymptotically stable coexistence equilibrium. Our results indicate that the basic reproduction numbers of both strains govern the overall dynamics, but in nontrivial ways due to the inclusion of cross-immunity. The model is applied to study the emergence of the SARS-CoV-2 Delta variant in the presence of the Alpha variant using wastewater surveillance data from the Deer Island Treatment Plant in Massachusetts, USA.

Updated analysis to reject the laboratory-engineering hypothesis of SARS-CoV-2.

A clear understanding of the origin of SARS-CoV-2 is important for future pandemic preparedness. Here, I provided an updated analysis of the type IIS endonuclease maps in genomes of alphacoronavirus, betacoronavirus, and SARS-CoV-2. Scenarios to engineer SARS-CoV-2 in the laboratory and the associated workload was also discussed. The analysis clearly shows that the endonuclease fingerprint does not indicate a synthetic origin of SARS-CoV-2 and engineering a SARS-CoV-2 virus in the laboratory is extremely challenging both scientifically and financially. On the contrary, current scientific evidence does support the animal origin of SARS-CoV-2.

Wide mismatches in the sequences of primers and probes for monkeypox virus diagnostic assays.

Rapid and accurate diagnosis of infections is fundamental to containment of disease. Several monkeypox virus (MPV) real-time diagnostic assays have been recommended by the CDC; however, the specificity of the primers and probes in these assays for the ongoing MPV outbreak has not been investigated. We analyzed the primer and probe sequences present in the CDC recommended MPV generic real-time PCR assay by aligning those sequences against 1730 MPV complete genomes reported in 2022 worldwide. Sequence mismatches were found in 99.08% and 97.46% of genomes for the MPV generic forward and reverse primers, respectively. Mismatch-corrected primers were synthetized and compared to the generic assay for MPV detection. Results showed that the two primer-template mismatches resulted in a ~11-fold underestimation of initial template DNA in the reaction and 4-fold increase in the 95% LOD. We further evaluated the specificity of seven other real-time PCR assays used for MPV and orthopoxvirus (OPV) detection and identified two assays with the highest matching score (>99.6%) to the global MPV genome database in 2022. Genetic variations in the primer-probe regions across MPV genomes could indicate the temporal and spatial emergence pattern of monkeypox disease. Our results show that the current MPV real-time generic assay may not be optimal to accurately detect MPV, and the mismatch-corrected assay with full complementarity between primers and current MPV genomes could provide a more sensitive and accurate detection of MPV.

A regulatory loop establishes the link between the circadian clock and abscisic acid signaling in rice.

There is a close regulatory relationship between the circadian clock and the abscisic acid (ABA) signaling pathway in regulating many developmental processes and stress responses. However, the exact feedback regulation mechanism between them is still poorly understood. Here, we identified the rice (Oryza sativa) clock component PSEUDO-RESPONSE REGULATOR 95 (OsPRR95) as a transcriptional regulator that accelerates seed germination and seedling growth by inhibiting ABA signaling. We also found that OsPRR95 binds to the ABA receptor gene REGULATORY COMPONENTS OF ABA RECEPTORS10 (OsRCAR10) DNA and inhibits its expression. Genetic analysis showed OsRCAR10 acts downstream of OsPRR95 in mediating ABA responses. In addition, the induction of OsPRR95 by ABA partly required a functional OsRCAR10, and the ABA-responsive element-binding factor ABSCISIC ACID INSENSITIVE5 (OsABI5) bound directly to the promoter of OsPRR95 and activated its expression, thus establishing a regulatory feedback loop between OsPRR95, OsRCAR10, and OsABI5. Taken together, our results demonstrated that the OsRCAR10-OsABI5-OsPRR95 feedback loop modulates ABA signaling to fine-tune seed germination and seedling growth, thus establishing the molecular link between ABA signaling and the circadian clock.

A simple SEIR-V model to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission using wastewater-based surveillance data.

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor SARS-CoV-2 transmission. However, epidemiological inference from WBS data remains understudied and limits its application. In this study, we have established a quantitative framework to estimate COVID-19 prevalence and predict SARS-CoV-2 transmission through integrating WBS data into an SEIR-V model. We conceptually divide the individual-level viral shedding course into exposed, infectious, and recovery phases as an analogy to the compartments in a population-level SEIR model. We demonstrated that the effect of temperature on viral losses in the sewer can be straightforwardly incorporated in our framework. Using WBS data from the second wave of the pandemic (Oct 02, 2020-Jan 25, 2021) in the Greater Boston area, we showed that the SEIR-V model successfully recapitulates the temporal dynamics of viral load in wastewater and predicts the true number of cases peaked earlier and higher than the number of reported cases by 6-16 days and 8.3-10.2 folds (R = 0.93). This work showcases a simple yet effective method to bridge WBS and quantitative epidemiological modeling to estimate the prevalence and transmission of SARS-CoV-2 in the sewershed, which could facilitate the application of wastewater surveillance of infectious diseases for epidemiological inference and inform public health actions.