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Background Ticks have been reported across China, but information on ticks from Chongming Eco-Island of Shanghai is lacking. Understanding the distribution and genetic evolution of ticks on the island is crucial for tick-borne infection control. Methods Ticks were collected from eight towns and four protected areas of Chongming Island during April 2021-March 2022 and were morphologically identified under microscopy. Molecular characterization of the ticks was performed by PCR amplification and sequencing of 12S rRNA and co1 mitochondrial genes. Homology analyses with published sequences obtained from GenBank were conducted for genetic relationships based on neighbor-joining (NJ) analysis of the 12S rRNA and co1 gene loci. To assess genetic evolution, intraspecific and interspecific genetic distances and barcoding gap were assessed based on NJ-K2P analysis of the 12S rRNA locus. Furthermore, genetic diversity and neutrality tests were performed on 12S rRNA sequences. Results A total of 1417/1933 ticks were successfully amplified by PCR of the 12S rRNA and co1 loci. Sequencing and homology analyses revealed four species of ticks, including Haemaphysalis flava (1376/1417 [97.11%], Ha. longicornis (37/1417 [2.61%]), Ha. doenitzi (3/1417 [0.21%]), and Ha. japonica (1/1417 [0.07%]). The intraspecies identity was 100% for Ha. longicornis, 99.11% for doenitzi, and 96.17%, while Ha. japonica had 83.48% intraspecies identity. Phylogenetic analyses showed species specificity, which clustered with homologous sequences. The average K2P distances between and within the species were 0.1351 (range 0.0723–0.1960) and 0.0145 (range 0-0.0946), respectively. The maximum K2P distance within species was in Ha. japonica (0.0946), while the maximum interspecific K2P distance was 0.1960 between Ha. hystricis and Ha. japonica. Genetic diversity indices and neutrality tests revealed that Fu and Li’s D and Tajima’s D values were negative for all species (mean values − 0.9360 and − 1.0310, respectively), suggesting evidence of recent population expansion. Conclusions This study is the first to report the genetic characterization of ticks from Chongming Eco-Island of Shanghai. We identified four species of Haemaphysalis ticks that were genetically similar to other congeners reported in China or worldwide. The knowledge gained from this study serves as a basis to support intervention deployment for effective control of tick-borne infections.

Background: Zoonoses are public health threats that cause severe damages worldwide and, constitute a key indicator of One Health (OH). The OH approach is being applied for control programmes of zoonotic diseases. In a very recent study, we have developed an evaluation system for OH performance through global OH index (GOHI). This study applied GOHI to evaluate OH performance for zoonoses in sub-Saharan Africa.Methods: Framework for OH index on zoonoses (OHIZ) was constructed including five indicators, 15 sub-indicators and 28 datasets. Publicly available data were referenced to generate OHIZ database which included both qualitative and quantitative indicators for all sub-Sahara African countries (n=48). GOHI algorithm was referred to estimate scores for OHIZ. Indicators weight was calculated by adopting the fuzzy analytical hierarchy process. Results: Overall, five indicators associated with weights were generated as follows: source of infection (23.70%), route of transmission (25.31%), targeted population (19.09%), capacity building (16.77%), and outcomes/case-studies (15.13%). Following the indicators, a total of 37 sub-Sahara African countries aligned with OHIZ validation, while 11 territories were excluded for unfit or missing data. The OHIZ average score of sub-Saharan Africa was estimated at 53.67/100. The highest score was 71.99 from South Africa, while the lowest score was 40.51 from Benin. It is also worth to be mentioned that Sub-Sahara African countries had high performance in many sub-indicators associated with zoonoses, e.g., surveillance and response, vector and reservoir interventions, and natural protected areas, which suggests this region had a certain capacity in control and prevention or responses to zoonotic events.Conclusion: This study reveals that it is possible to perform the OH evaluation for zoonoses in sub-Saharan Africa by OHIZ. Findings from this study provide preliminary research information in advancing knowledge of the evidenced-risks to strengthen strategies for effective control of zoonoses and to support the prevention of zoonotic events.

Insulin/IGF-1 Signaling (IIS) constrains longevity by inhibiting the transcription factor FOXO. Beyond FOXO, little is known about how phosphorylation—as mediated by IIS kinases— regulates lifespan. Here, we profiled IIS-dependent phosphorylation changes in a large-scale quantitative phosphoproteomic analysis of wild-type and three IIS mutant C. elegans strains. Our state-of-the-art analysis experimentally identified more than 15,000 phosphosites, among which 448 were differentially phosphorylated in the long-lived daf-2/insulin receptor mutant. We developed a machine-learning-based tool for systematically ranking the likely functional importance of phosphosites to guide candidate selection for follow-up validation. We show that AKT-1 pT492 inhibits DAF-16/FOXO and compensates the loss of daf-2 function, that EIF-2α pS49 potently regulates protein synthesis and daf-2 longevity, and that reduced phosphorylation of multiple germline proteins (e.g., CDK-1) apparently transmits a signal representing reduced DAF-2 signaling to the soma. Finally, kinase-substrate analysis and subsequent experimental validation confirm that casein kinase 2 negatively regulates lifespan. Our new benchmark data resource and machine-learning tool enables unprecedented access to detailed functional insights for studies of longevity.