Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally

SUMO regulates p21Cip1 intracellular distribution and with p21Cip1 facilitates multiprotein complex formation in the nucleolus upon DNA damage

We previously showed that p21Cip1 transits through the nucleolus on its way from the nucleus to the cytoplasm and that DNA damage inhibits this transit and induces the formation of p21Cip1-containing intranucleolar bodies (INoBs). Here, we demonstrate that these INoBs also contain SUMO-1 and UBC9, the E2 SUMO-conjugating enzyme. Furthermore, whereas wild type SUMO-1 localized in INoBs, a SUMO-1 mutant, which is unable to conjugate with proteins, does not, suggesting the presence of SUMOylated proteins at INoBs. Moreover, depletion of the SUMO-conjugating enzyme UBC9 or the sumo hydrolase SENP2 changed p21Cip1 intracellular distribution. In addition to SUMO-1 and p21Cip1, cell cycle regulators and DNA damage checkpoint proteins, including Cdk2, Cyclin E, PCNA, p53 and Mdm2, and PML were also detected in INoBs. Importantly, depletion of UBC9 or p21Cip1 impacted INoB biogenesis and the nucleolar accumulation of the cell cycle regulators and DNA damage checkpoint proteins following DNA damage. The impact of p21Cip1 and SUMO-1 on the accumulation of proteins in INoBs extends also to CRM1, a nuclear exportin that is also important for protein translocation from the cytoplasm to the nucleolus. Thus, SUMO and p21Cip1 regulate the transit of proteins through the nucleolus, and that disruption of nucleolar export by DNA damage induces SUMO and p21Cip1 to act as hub proteins to form a multiprotein complex in the nucleolus