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La dependencia del celular se conoce como la necesidad de tener acceso a un dispositivo móvil en una determina situación, esto aparece con mayor frecuencia en los adolescentes debido a la época de transición que están pasando. El tener acceso a un celular permite una conexión amplia a redes sociales, internet o video juegos que pueden generar una adicción y varios problemas psicológicos. Se llevó a cabo una investigación descriptiva y comparativa, de corte transversal, para lo cual se utilizó una muestra de 204 adolescentes en donde el 44.1% fueron mujeres y el 55.9% hombres, con una media de 15,46 años; se utiliza la prueba de Dependencia al Móvil de Chóliz (TDM). Los resultados obtenidos indican una diferencia significativa del nivel de dependencia al celular para el GS (30.30) fue significativamente distinta que el GP (21.43) (t(190)= -4.55, p

Chronic lower respiratory tract infections are a leading contributor to morbidity and mortality in persons with cystic fibrosis (pwCF). Traditional respiratory tract surveillance culturing has focused on a limited range of classic pathogens; however, comprehensive culture and culture-independent molecular approaches have demonstrated complex communities highly unique to each individual. Microbial community structure evolves through the lifetime of pwCF and is associated with baseline disease state and rates of disease progression including occurrence of pulmonary exacerbations. While molecular analysis of the airway microbiome has provided insight into these dynamics, challenges remain including discerning not only “who is there” but “what they are doing” in relation to disease progression. Moreover, the microbiome can be leveraged as a multi-modal biomarker for both disease activity and prognostication. In this article, we review our evolving understanding of the role these communities play in pwCF and identify challenges in translating microbiome data to clinical practice.

Al abordar la problemática de la inequidad de género en los cargos públicos, es posible afirmar que, a pesar de la violación constante de derechos que han sufrido estos dos grupos a lo largo de la historia, hoy en día gozan con mayor participación en los altos niveles decisorios de las ramas del poder público. Sin embargo, el esfuerzo tanto de las mujeres como de la comunidad lgbt de participar en los procesos democráticos se ve quebrantado por la falta de aplicación de las políticas públicas destinadas a contrarrestar dicha problemática. En el contexto de la actual coyuntura generada por la pandemia de la covid-19, las mujeres y las personas pertenecientes al colectivo lgbt han tenido menos oportunidades de desarrollarse en el ámbito laboral, con lo que se ha agudizado la diferencia entre hombres y mujeres en distintos campos de la sociedad, brecha que se hace evidente incluso en las esferas del poder público. Por ello, nuestra investigación responderá a la pregunta problema: ¿cómo la inequidad de género en los cargos públicos simboliza una transgresión para los derechos de las mujeres y de la comunidad lgbt en Colombia? Por tanto, se realizará un análisis de la inequidad de género en los cargos públicos como factor determinante para la transgresión de los derechos de las mujeres y de la comunidad lgbt. Se abordan tres objetivos específicos: (i) describir la evolución de la participación efectiva de las mujeres y de la comunidad lgbt en los cargos públicos en Colombia; (ii) identificar los factores que transgreden la participación igualitaria en los cargos públicos; y (iii) comparar en materia de derecho las medidas aplicadas en Suecia y Colombia para contrarrestar la inequidad de género en los cargos públicos.

The severity and progression of lung disease are highly variable across individuals with cystic fibrosis (CF) and are imperfectly predicted by mutations in the human gene CFTR, lung microbiome variation or other clinical factors. The opportunistic pathogen Pseudomonas aeruginosa (Pa) dominates airway infections in most CF adults. Here we hypothesized that within–host genetic variation of Pa populations would be associated with lung disease severity. To quantify Pa genetic variation within CF sputum samples, we used deep amplicon sequencing (AmpliSeq) of 209 Pa genes previously associated with pathogenesis or adaptation to the CF lung. We trained machine learning models using Pa single nucleotide variants (SNVs), microbiome diversity data and clinical factors to classify lung disease severity at the time of sputum sampling, and to predict lung function decline after 5 years in a cohort of 54 adult CF patients with chronic Pa infection. Models using Pa SNVs alone classified lung disease severity with good sensitivity and specificity (area under the receiver operating characteristic curve: AUROC=0.87). Models were less predictive of lung function decline after 5 years (AUROC=0.74) but still significantly better than random. The addition of clinical data, but not sputum microbiome diversity data, yielded only modest improvements in classifying baseline lung function (AUROC=0.92) and predicting lung function decline (AUROC=0.79), suggesting that Pa AmpliSeq data account for most of the predictive value. Our work provides a proof of principle that Pa genetic variation in sputum tracks lung disease severity, moderately predicts lung function decline and could serve as a disease biomarker among CF patients with chronic Pa infections.

UV-LED irradiation has attracted attention in water and wastewater disinfection applications. However, no studies have quantitatively investigated the impact of light intensity on the UV dosage for the same magnitude of disinfection. This study presents a powerful 280 nm UV-LED photoreactor with adjustable light intensity to disinfect municipal wastewater contaminated with E. coli, SARS-CoV-2 genetic materials and others. The disinfection performance of the 280 nm LED was also compared with 405 nm visible light LEDs, in terms of inactivating E. coli and total coliforms, as well as reducing cATP activities. The results showed that the UV dose needed per log reduction of E. coli and total coliforms, as well as cATP, could be decreased by increasing the light intensity within the investigated range (0–9640 µW/cm2). Higher energy consumption is needed for microbial disinfection using the 405 nm LED when compared to 280 nm LED. The signal of SARS-CoV-2 genetic material in wastewater and the SARS-CoV-2 spike protein in pure water decreased upon 280 nm UV irradiation.

Antimicrobial resistance (AMR) is an ever-increasing threat to global health. Wastewater-based surveillance is an emerging methodology that objectively enables an inclusive and comprehensive assessment of population AMR in an observed sewershed. Here we compared the resistome of two tertiary-care hospitals with two separate neighborhoods, using complimentary targeted qPCR and metagenomics of wastewater before and after selective culture enrichment for clinically important Gram negatives. In total 26 ARG-type (1225 ARG-subtypes) were found across all samples, in which β-lactam ARG was the richest (the number of different ARG-subtypes found) followed by multidrug, fluoroquinolone, macrolide-lincosamide-streptogramin (MLS) and aminoglycoside. The composition of ARGs in wastewater differed between raw wastewater pellets and culture-enriched wastewater samples and the resistomes clustered based on the type of location (Hospitals vs neighborhoods). Hospital wastewater was found to have higher diversity and greater abundance of ARGs compared to neighborhood wastewater when the composition profiles of ARGs in both raw and culture-enriched wastewater pellets. Clinically relevant ARG (i.e., VIM, NDM metallo-ß-lactamases) were detected in culture enrichment samples that were not identified in raw samples, despite a lower targeted sequencing depth. Wastewater-based surveillance is an effective, and potentially extremely important and powerful tool that could be developed to augment hospital-based infection control and antimicrobial stewardship programs, creating a safer space for those receiving care.

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this technology has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021-April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary’s campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites – regardless of several normalization strategies – with certain catchments consistently demonstrating values 1–2 orders higher than the others. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.01). Real-time contact tracing data was used to confirm an association between wastewater SARS-CoV-2 burden and clinically confirmed cases proving the potential of WBS as a tool for disease monitoring across worksites. Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.Synopsis‘This study establishes that wastewater-based surveillance with a node-based sampling strategy can be used to passively monitor for disease, locate disease “hotspots” and approximate the burden of infected individuals’

Wastewater-based surveillance (WBS) is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19’s impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with local workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.3 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5% (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4,524 unrelated absences COVID-19 cases were recorded. Employee absences significantly increased as wastewater signal increased through the pandemic’s waves. Strong correlations between COVID-19-confirmed absences and wastewater SARS-CoV-2 signals (N1 gene: r=0.824, p2-value demonstrated a robust association (adjusted R2=0.783), when adjusted by 7 days, indicating wastewater provides a one-week leading signal. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (PHighlightsWBS is a useful strategy for monitoring infectious diseases in workersSARS-CoV-2 RNA in wastewater correlated with workforce absenteeismWorkplace absenteeism secondary to COVID-19 can be predicted using WBSWBS can be used by employers to anticipate and mitigate work force absenteeismGraphical abstract

Wastewater-based SARS-CoV-2 surveillance enables unbiased and comprehensive monitoring of defined sewersheds. We performed real-time monitoring of hospital wastewater that differentiated Delta and Omicron variants within total SARS-CoV-2-RNA, enabling correlation to COVID-19 cases from three tertiary-care facilities with2100 inpatient beds in Calgary, Canada. RNA was extracted from hospital wastewater between August/2021 and January/2022, and SARS-CoV-2 quantified using RT-qPCR. Assays targeting R203M and R203K/G204R established the proportional abundance of Delta and Omicron, respectively. Total and variant-specific SARS-CoV-2 in wastewater was compared to data for variant specific COVID-19 hospitalizations, hospital-acquired infections, and outbreaks. Ninety-six percent (188/196) of wastewater samples were SARS-CoV-2 positive. Total SARS-CoV-2 RNA levels in wastewater increased in tandem with total prevalent cases (Delta plus Omicron). Variant-specific assessments showed this increase to be mainly driven by Omicron. Hospital-acquired cases of COVID-19 were associated with large spikes in wastewater SARS-CoV-2 and levels were significantly increased during outbreaks relative to non-outbreak periods for total SARS-CoV2, Delta and Omicron. SARS-CoV-2 in hospital wastewater was significantly higher during the Omicron-wave irrespective of outbreaks. Wastewater-based monitoring of SARS-CoV-2 and its variants represents a novel tool for passive COVID-19 infection surveillance, case identification, containment, and potentially to mitigate viral spread in hospitals. This article is protected by copyright. All rights reserved.

Background WW surveillance enables real time monitoring of SARS-CoV-2 burden in defined sewer catchment areas. Here, we assessed the occurrence of total, Delta and Omicron SARS-CoV-2 RNA in sewage from three tertiary-care hospitals in Calgary, Canada. Methods Nucleic acid was extracted from hospital (H) WW using the 4S-silica column method. H-1 and H-2 were assessed via a single autosampler whereas H-3 required three separate monitoring devices (a-c). SARS-CoV-2 RNA was quantified using two RT-qPCR approaches targeting the nucleocapsid gene; N1 and N200 assays, and the R203K/G204R and R203M mutations. Assays were positive if Cq< 40. Cross-correlation function analyses (CCF) was performed to determine the time-lagged relationships between WW signal and clinical cases. SARS-CoV-2 RNA abundance was compared to total hospitalized cases, nosocomial-acquired cases, and outbreaks. Statistical analyses were conducted using R. Results Ninety-six percent (188/196) of WW samples collected between Aug/21-Jan/22 were positive for SARS-CoV-2. Omicron rapidly supplanted Delta by mid-December and this correlated with lack of Delta-associated H-transmissions during a period of frequent outbreaks. The CCF analysis showed a positive autocorrelation between the RNA concentration and total cases, where the most dominant cross correlations occurred between -3 and 0 lags (weeks) (Cross-correlation values: 0.75, 0.579, 0.608, 0.528 and 0.746 for H-1, H-2, H-3a, H-3b and H-3c; respectively). VOC-specific assessments showed this positive association only to hold true for Omicron across all hospitals (cross-correlation occurred at lags -2 and 0, CFF value range between 0.648 -0.984). We observed a significant difference in median copies/ml SARS-CoV-2 N-1 between outbreak-free periods vs outbreaks for H-1 (46 [IQR: 11-150] vs 742 [IQR: 162-1176], P< 0.0001), H-2 (24 [IQR: 6-167] vs 214 [IQR: 57-560], P=0.009) and H-3c (2.32 [IQR: 0-19] vs 129 [IQR: 14-274], P=0.001). Conclusion WW surveillance is a powerful tool for early detection and monitoring of circulating SARS-CoV-2 VOCs. Total SARS-CoV-2 and VOC-specific WW signal correlated with hospitalized prevalent cases of COVID-19 and outbreak occurrence. Disclosures All Authors: No reported disclosures.

Background Universities are interactive communities where frequent contacts between individuals occur, increasing the risk of outbreaks of COVID-19. We embarked upon a real-time wastewater (WW) monitoring program across the University of Calgary (UofC) campus measuring WW SARS-CoV-2 burden relative to levels of disease in the broader surrounding community. Figure 1 The colour scheme shows 6 sewer sub-catchments at the University of Calgary. Autosamplers were deployed at 4 sampling nodes within sub-catchments CR and YA (both residence halls), and UCE and UCS (catchments that include several campus buildings). Figure 2 Log10-transformed abundance (i.e., copies per mL) of nucleocapsid gene (i.e., N1) for SARS-CoV-2 for each sampling location during October 2021 – April 2022. Locations denoted by the same letters (A, B, or C) show no statistical difference (p > 0.05) according to the Wilcoxon rank-sum test. The WWTP sample corresponds to a catchment area covering most of Calgary including the university campus, for which sampling locations CR, UCE, UCS, and UCW are defined in Fig. 1. Methods From October 2021 – April 2022, WW was collected thrice weekly across UofC campus through 4 individual sewer sampling nodes (Fig. 1) using autosamplers (C.E.C. Analytics, CA). Results from these 4 nodes were compared with community monitoring at Calgary’s largest WW treatment plant (WWTP), which received WW from surrounding neighborhoods, and also from UofC. Nucleic acid was extracted from WW for RTqPCR quantification of the N1 nucleocapside gene from SARS-CoV-2 genomic RNA. Qualitative (positive samples defined if cycle threshold < 40) and quantitative statistical analyses were performed using R. Results Levels of SARS-CoV-2 in WW were significantly lower at all campus monitoring sites relative to the WWTP (Wilcoxon rank-sum test p < 0.05; Fig. 2). The proportion of WW samples that were positive for SARS-CoV-2 was significantly higher for WWTP than at least two campus locations (p < 0.05 for Crowsnest Hall and UCE - University way and campus drive) according to Fischer’s exact 2-sided test. The proportion of WW samples with positive WW signals were still higher for WWTP than the other two locations, but statistically not significant (p = 0.216). Among campus locations, the buildings in UCE catchment showed much lower N1 signals than other catchments, likely owing to buildings in this catchment primarily being administration and classroom environments, with lower human-to-human contact and less defecation compared to the other 3 catchments, which include residence hall, a dining area, and/or laboratory spaces. Conclusion Our results show that SARS-CoV-2 RNA shedding in WW at the UofC is significantly lower than the city-wide signal associated with surrounding neighborhoods. Furthermore, we demonstrate that WW testing at well-defined nodes is a sampling strategy for potentially locating specific places where high transmission of infectious disease occurs. Disclosures All Authors: No reported disclosures.

Background New tools capable of dynamic assessment of the varying burden of Clostridioides difficile infections are required to mitigate increased patient morbidity, mortality, and health costs. Wastewater (WW)-based epidemiology (WBE) is an emerging science, enabling comprehensive, inclusive, and unbiased assessment of populations, spatially and temporally. We sought to detect, quantify and track C. difficile across a range of scales using WBE. Methods WW collected from two hospitals; the Rockyview General Hospital (RGH; 600 beds) and Peter Lougheed Centre (PLC; 550 beds) both based in Calgary, were compared to that from a municipal WW Treatment Plant (WWTP) in Calgary, Canada. DNA was extracted from pellets collected after WW centrifugation. A multiplexed quantitative PCR assay was used to quantify the abundance of C. difficile 16S rRNA and toxin A (tcdA) genes. These were then assessed as raw values or as normalized ratios to three fecal biomarker genes: total bacterial 16S rRNA, human 18S rRNA, and Bacteroides HF183 16S rRNA. Kruskal-Wallis and Mann-Whitney tests were performed using RStudio and GraphPad Prism (version 9.3.1). Results Eight weekly samples collected from the RGH demonstrated significant changes in the levels of total C. difficile 16S rRNA gene and tcdA over time (P=0.0004 and P=0.0005, respectively, Kruskal-Wallis). Similar trends in total C. difficile and tcdA burden over time were observed when gene copies were normalized with the three fecal biomarker genes. Over a separate 13-week comparison, C. difficile and tcdA gene target abundance was greater in hospital WW (RGH and PLC) than in community-based samples from the WWTP (P=0.048 and P=0.012, respectively, Mann-Whitney). There was no significant difference in C. difficile and tcdA gene target abundance between RGH and PLC (P=0.896 and P=0.343, respectively, Mann-Whitney). Clostridioides difficile genes in wastewater measured by quantitative PCR. C. difficile 16S rRNA and tcdA gene abundance normalized as a ratio against total bacterial load (16S rRNA) varies over time and is markedly increased in hospitals relative to a municipal wastewater treatment plant in Calgary, Canada. Conclusion WW surveillance is a powerful tool that can monitor the burden the C. difficile across a range of scales in real-time. This tool could augment infection prevention and control and antimicrobial stewardship programs to better understand factors that contribute to colonization and infection. Disclosures Thomas J. Louie, MD, Artugen: Advisor/Consultant|Artugen: Grant/Research Support|Crestone: Advisor/Consultant|Crestone: Grant/Research Support|Finch Therapeutics: Advisor/Consultant|Finch Therapeutics: Grant/Research Support|Rebiotix: Advisor/Consultant|Rebiotix: Grant/Research Support|Seres Therapeutics: Advisor/Consultant|Seres Therapeutics: Grant/Research Support|summit plc: Advisor/Consultant|summit plc: Grant/Research Support|Vedanta Biosciences: Advisor/Consultant|Vedanta Biosciences: Grant/Research Support.

Background We sought to compare WW SARS-CoV-2 RNA detection across a range of sites and scales using RTqPCR and RTddPCR. Figure. Methods Composite-24h WW was collected from a WW treatment plant (WTP; n=18), a neighborhood (Nb1; n=12) and three hospitals; H-1, H-2, and H-3 (3-sites; A-C)(n=84). RNA was extracted using the 4S-silica column method. RTqPCR (QuantStudio5, ThermoFisher) and RTddPCR (C1000 Thermal Cycler and QX200 Droplet Reader, BioRad) quantified SARS-CoV-2 RNA nucleocapsid (N2, US CDC) and envelope (E Sarbeco, Corman et al 2020) in triplicate. Fisher’s exact test was used to compare assay sensitivity. Correlations between modalities and RNA - clinically-confirmed COVID-19 cases (defined by postal code of primary residence using 5-day rolling average) was assessed using Persons correlation. Results 114 samples were tested (02/23/2021-04/22/2021). SARS-CoV-2-N2 was identified in 90/114 (79%) by RTqPCR and 89/114 (78%) by ddPCR (p=1). SARS-CoV-2 E was found in 72/114 (63%) by RTqPCR and 90/114 (79%) by ddPCR, p=0.01. Correlations between modalities were strongest for N2 relative to E across all sites (see Table). N2 correlated with clinically diagnosed cases for both modalities greater at the level of the WTP (RTqPCR; r=0.8972, p< 0.0001and ddPCR; 0.933, p< 0.0001) relative to neighborhood (RTqPCR; r=0.6, p=0.04 and ddPCR; 0.60, p=0.04). E correlated to a lesser degree with cases at WTP (RTqPCR; r=0.65, p=0.0035 and ddPCR; 0.88, p=< 0.001) and neighborhoods (RTqPCR; r=0.40, p=0.20 and ddPCR; r=0.43, p=0.16). Conclusion SARS-CoV-2 detection of N2 was similar between RTqPCR and RTddPCR across a range of sites and scales in the sewershed, and this correlated best with clinical cases whereas E detection was superior with ddPCR. Disclosures All Authors: No reported disclosures.

BackgroundInhaled tobramycin powder/solution (TIP/S) use has resulted in improved clinical outcomes in patients with cystic fibrosis (CF) with chronic Pseudomonas aeruginosa. However, TIP/S effect on the CF sputum microbiome has not been explored. We hypothesised that TIP/S has additional ‘off-target’ effects beyond merely P. aeruginosa and that baseline microbiome prior to initiation of therapy is associated with subsequent patient response.MethodsWe drew sputum samples from a prospectively collected biobank. Patients were included if they had one sputum sample in the 18 months before and after TIP/S. Bacterial 16S rRNA gene profiling was used to characterise the sputum microbiome.ResultsForty-one patients met our inclusion criteria and 151 sputum samples were assessed. At baseline, median age was 30.4 years (IQR 24.2–35.2) and forced expiratory volume in 1 (FEV1) second was 57% predicted (IQR 44–74). Nineteen patients were defined a priori as responders having no net decrease in FEV1 in the year following TIP/S. No significant changes were observed in key microbiome metrics of alpha (within-sample) or beta (between-sample) diversity for samples collected before and after TIP/S. However, significant beta-diversity (Bray-Curtis) differences were noted at baseline between patients based on response status. Notably, responders were observed to have a higher abundance of Staphylococcus in pretherapy baseline samples.ConclusionsOur longitudinal study demonstrates that the sputum microbiome of patients with CF is relatively stable following inhaled tobramycin over many months. Intriguingly, our findings suggest that baseline microbiome may associate with patient response to TIP/S—suggesting the sputum microbiome could be used to personalise therapy.

Wastewater monitoring of SARS-CoV-2 allows for early detection and monitoring of COVID-19 burden in communities and can track specific variants of concern. Targeted assays enabled relative proportions of SARS-CoV-2 Omicron and Delta variants to be determined across 30 municipalities covering >75% of the province of Alberta (pop. 4.5M) in Canada, from November 2021 to January 2022. Larger cities like Calgary and Edmonton exhibited a more rapid emergence of Omicron relative to smaller and more remote municipalities. Notable exceptions were Banff, a small international resort town, and Fort McMurray, a more remote northern city with a large fly-in worker population. The integrated wastewater signal revealed that the Omicron variant represented close to 100% of SARS-CoV-2 burden prior to the observed increase in newly diagnosed clinical cases throughout Alberta, which peaked two weeks later. These findings demonstrate that wastewater monitoring offers early and reliable population-level results for establishing the extent and spread of emerging pathogens including SARS-CoV-2 variants.

With growing concerns linked to the (un)sustainable management of forest resources, the role of institutions as mediators increasingly gains relevance in sub-Saharan Africa (SSA). This is particularly so, as formal and informal institutions virtually compete for dominance – a yet-to-be-resolved colonial hangover. A large body of scientific knowledge exists on the role of institutions in regulating forest access, use, and management in SSA, albeit fragmented. Sub-regional variations in research on this subject further nuances our understanding of the breadth of conceptual and methodological issues in this field. This raises a central question: How can we advance knowledge on forest management institutions in SSA to enhance forest governance amidst the critical role of forests in addressing current global environmental challenges? We contribute answers to such interrogation by systematically reviewing more than three decades of scientific literature on institutions in forest use and management. Through a structured review of 100 empirical articles (involving 374 cases studies), and guided by the socio-ecological co-evolution framework, we derived two lessons. First, the conceptualization of forest-linked institutions is more skewed towards institutions as processes, than as structures. Second, the major determinants of institutional compliance are economic, ecological, political, socio-cultural, demographic, and geographical in nature. However, the weight of each determining factor varies in specific sub-regions. For instance, in East Africa, economic, ecological, socio-cultural, and geographic factors dominate while economic, demographic, and political factors dominate in Central Africa. Therefore, in crafting forest Institutions in SSA, sub-regional disparities in factors that influence compliance (or otherwise) should be critically considered and addressed to improve effectiveness. Methodologically, qualitative approaches (e.g., key informant interviews and focus group discussions), conducted within short time spans, have been prioritized. However, observed knowledge fragmentation on the subject, including inconsistencies or mismatches, calls for combined, long term qualitative analyses with quantitative ones, in a robust mixed-methods approach. Future research should prioritize this methodological approach, with a focus on sub-regional, country-level specificities, to better inform understanding of forest-linked institutional dynamics.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.3 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December, 2020) and the third-wave of the COVID-19 pandemic (mid-April to May, 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06 % (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals’ primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1 & N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary’s three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

Complex polymicrobial communities inhabit the lungs of individuals with cystic fibrosis (CF) and contribute to the decline in lung function. However, the severity of lung disease and its progression in CF patients are highly variable and imperfectly predicted by host clinical factors at baseline, CFTR mutations in the host genome, or sputum polymicrobial community variation. The opportunistic pathogen Pseudomonas aeruginosa (Pa) dominates airway infections in the majority of CF adults. Here we hypothesized that genetic variation within Pa populations would be predictive of lung disease severity. To quantify Pa genetic variation within whole CF sputum samples, we used deep amplicon sequencing on a newly developed custom Ion AmpliSeq panel of 209 Pa genes previously associated with the host pathoadaptation and pathogenesis of CF infection. We trained machine learning models using Pa single nucleotide variants (SNVs), clinical and microbiome diversity data to classify lung disease severity at the time of sputum sampling, and to predict future lung function decline over five years in a cohort of 54 adult CF patients with chronic Pa infection. The models using Pa SNVs alone classified baseline lung disease with good sensitivity and specificity, with an area under the receiver operating characteristic curve (AUROC) of 0.87. While the models were less predictive of future lung function decline, they still achieved an AUROC of 0.74. The addition of clinical data to the models, but not microbiome community data, yielded modest improvements (baseline lung function: AUROC=0.92; lung function decline: AUROC=0.79), highlighting the predictive value of the AmpliSeq data. Together, our work provides a proof-of-principle that Pa genetic variation in sputum is strongly associated with baseline lung disease, moderately predicts future lung function decline, and provides insight into the pathobiology of Pa’s effect on CF.ImportanceCystic fibrosis (CF) is among the most common, life-limiting inherited disorder, caused by mutations in the CF transmembrane conductance regulator (CFTR) gene. CF causes progressive damage to the lungs, the major cause of morbidity and mortality in CF patients. However, the rate of lung function decline is highly variable across CF patients, and cannot be fully explained using existing biomarkers in the human genome or patient co-morbidities. Pseudomonas aeruginosa (Pa) is known to evolve and adapt within chronic CF infections. We hypothesized that within-patient Pa diversity could affect lung disease severity. In a CF cohort study, we demonstrate the utility of machine learning tools for predictive modeling of baseline lung function and subsequent decline in CF patients using deep within-patient Pa amplicon sequencing. Our findings show the potential of these models to identify high-risk CF patients based on Pa diversity within the lung.

SARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals. Between August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling >2100 dedicated inpatient beds) were collected. Hospital-1 and Hospital-2 could be captured with a single sampling point whereas Hospital-3 required three separate monitoring sites. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks. Of 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of the amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations at those sites with single monitoring points (Pearson's r=0.679, P, Graphical Abstract Image, graphical abstract

Background Azithromycin is commonly prescribed drug for individuals with cystic fibrosis (CF), with demonstrated benefits in reducing lung function decline, exacerbation occurrence and improving nutrition. As azithromycin has antimicrobial activity against components of the uncultured microbiome and increasingly the CF microbiome is implicated in disease pathogenesis – we postulated azithromycin may act through its manipulation. Herein we sought to determine if the CF microbiome changed following azithromycin use and if clinical benefit observed during azithromycin use associated with baseline community structure. Results Drawing from a prospectively collected biobank we identified patients with sputum samples prior to, during and after initiating azithromycin and determined the composition of the CF microbial community by sequencing the V3-V4 region of the 16S rRNA gene. We categorized patients as responders if their rate of lung function decline improved after azithromycin initiation. Thirty-eight adults comprised our cohort, nine who had not utilized azithromycin in at least 3 years, and 29 who were completely naïve. We did not observe a major impact in the microbial community structure of CF sputum in the 2 years following azithromycin usage in either alpha or beta-diversity metrics. Seventeen patients (45%) were classified as Responders – demonstrating reduced lung function decline after azithromycin. Responders who were naïve to azithromycin had a modest clustering effect distinguishing them from those who were non-Responders, and had communities enriched with several organisms including Stenotrophomonas, but not Pseudomonas. Conclusions Azithromycin treatment did not associate with subsequent large changes in the CF microbiome structure. However, we found that baseline community structure associated with subsequent azithromycin response in CF adults.

BackgroundSARS-CoV-2 has been detected in wastewater and its abundance correlated with community COVID-19 cases, hospitalizations and deaths. We sought to use wastewater-based detection of SARS-CoV-2 to assess the epidemiology of SARS-CoV-2 in hospitals.MethodsBetween August and December 2020, twice-weekly wastewater samples from three tertiary-care hospitals (totaling >2100 dedicated inpatient beds) were collected. Wastewater samples were concentrated and cleaned using the 4S-silica column method and assessed for SARS-CoV-2 gene-targets (N1, N2 and E) and controls using RT-qPCR. Wastewater SARS-CoV-2 as measured by quantification cycle (Cq), genome copies and genomes normalized to the fecal biomarker PMMoV were compared to the total daily number of patients hospitalized with active COVID-19, confirmed cases of hospital-acquired infection, and the occurrence of unit-specific outbreaks.ResultsOf 165 wastewater samples collected, 159 (96%) were assayable. The N1-gene from SARS-CoV-2 was detected in 64.1% of samples, N2 in 49.7% and E in 10%. N1 and N2 in wastewater increased over time both in terms of amount of detectable virus and the proportion of samples that were positive, consistent with increasing hospitalizations (Pearson’s r=0.679, PConclusionsWastewater-based monitoring of SARS-CoV-2 represents a promising tool for SARS-CoV-2 passive surveillance and case identification, containment, and mitigation in acute-care medical facilities.Supplemental Material includedKey-points summarySAS-CoV-2 RNA is detectable in hospital wastewater. Wastewater SARS-CoV-2 RNA increases in conjunction with COVID-19-related hospitalizations. Spikes in SARS-CoV-2 wastewater signal correspond to incident hospital-acquired cases and outbreaks, suggesting passive surveillance via wastewater has great promise for COVID-19 monitoring.

Wastewater-based epidemiology (WBE) is an emerging surveillance tool that has been used to monitor the ongoing COVID-19 pandemic by tracking SARS-CoV-2 RNA shed into wastewater. WBE was performed to monitor the occurrence and spread of SARS-CoV-2 from three wastewater treatment plants (WWTP) and six neighborhoods in the city of Calgary, Canada (population 1.44 million). A total of 222 WWTP and 192 neighborhood samples were collected from June 2020 to May 2021, encompassing the end of the first-wave (June 2020), the second-wave (November end to December 2020) and the third-wave of the COVID-19 pandemic (mid-April to May 2021). Flow-weighted 24-hour composite samples were processed to extract RNA that was then analyzed for two SARS-CoV-2-specific regions of the nucleocapsid gene, N1 and N2, using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Using this approach SARS-CoV-2 RNA was detected in 98.06% (406/414) of wastewater samples. SARS-CoV-2 RNA abundance was compared to clinically diagnosed COVID-19 cases organized by the three-digit postal code of affected individuals' primary residences, enabling correlation analysis at neighborhood, WWTP and city-wide scales. Strong correlations were observed between N1N2 gene signals in wastewater and new daily cases for WWTPs and neighborhoods. Similarly, when flow rates at Calgary's three WWTPs were used to normalize observed concentrations of SARS-CoV-2 RNA and combine them into a city-wide signal, this was strongly correlated with regionally diagnosed COVID-19 cases and clinical test percent positivity rate. Linked census data demonstrated disproportionate SARS-CoV-2 in wastewater from areas of the city with lower socioeconomic status and more racialized communities. WBE across a range of urban scales was demonstrated to be an effective mechanism of COVID-19 surveillance.

BackgroundComplex polymicrobial communities infect cystic fibrosis (CF) lower airways. Generally, communities with low diversity, dominated by classical CF pathogens, associate with worsened patient status at sample collection. However, it is not known if the microbiome can predict future outcomes. We sought to determine if the microbiome could be adapted as a biomarker for patient prognostication.MethodsWe retrospectively assessed prospectively collected sputum from a cohort of 104 individuals aged 18–22 to determine factors associated with progression to early end-stage lung disease (eESLD; death/transplantation −3%/year FEV1over the ensuing 5 years). Illumina MiSeq paired-end sequencing of the V3-V4 region of the 16S rRNA was used to define the airway microbiome.ResultsBased on the primary outcome analysed, 17 individuals (16%) subsequently progressed to eESLD. They were more likely to have sputum with low alpha diversity, dominated by specific pathogens includingPseudomonas. Communities with abundantStreptococcuswere observed to be protective. Microbial communities clustered together by baseline lung disease stage and subsequent progression to eESLD. Multivariable analysis identified baseline lung function and alpha diversity as independent predictors of eESLD. For the secondary outcomes, 58 and 47 patients were classified as rapid progressors based on absolute and relative definitions of lung function decline, respectively. Patients with low alpha diversity were similarly more likely to be classified as experiencing rapid lung function decline over the ensuing 5 years when adjusted for baseline lung function.ConclusionsWe observed that the diversity of microbial communities in CF airways is predictive of progression to eESLD and disproportionate lung function decline and may therefore represent a novel biomarker.

The cystic fibrosis (CF) airways are infected with a diverse polymicrobial community.Understanding how changes in the CF microbiome have occurred over time, similar to the observed changes in the prevalence of cultured pathogens, is key in understanding the microbiome's role in disease.Drawing from a prospectively collected and maintained sputum biobank, we identified 45 patients with sputum samples collected between the ages of 18 and 21 years in three successive cohorts of adults transitioning to our CF clinic: A (1997-2000), B (2004-2007), and C (2010-2013). Patient demographics, clinical status, and medications were collected from detailed chart review. Microbial communities were assessed by Ilumina MiSeq sequencing of the variable 3 (V3) region of the 16S rDNA.The three cohorts were similar with respect to baseline demographics. There was a trend toward improved health and use of disease-modifying therapies in each successive cohort. Shannon diversity increased in the most recent cohort, suggesting an increase in the diversity of organisms between cohorts. Furthermore, the proportion of samples with Pseudomonas-dominated communities decreased over time, whereas Streptococcus increased. Although β-diversity was associated with transition cohort, the greatest predictor of diversity remained lung function. Furthermore, core microbiome constituents were preserved across cohorts.Modest changes in the composition and structure of the microbiome of three successive cohorts of young adults with CF were observed, occurring in parallel with successive improvements in clinical status. Importantly, however, the core microbiome constituents were preserved across cohorts.

Pseudomonas aeruginosa is the archetypal cystic fibrosis (CF) pathogen. However, the clinical course experienced by infected individuals varies markedly. Understanding these differences is imperative if further improvements in outcomes are to be achieved. Multiple studies have found that patients infected with epidemic P. aeruginosa (ePA) strains may have a worse clinical prognosis than those infected with unique, non-clonal strains. Additionally, the traditionally uncultured CF lung bacterial community (i.e., CF microbiome) may further influence the outcome. We sought to identify if these two important variables, not identified through routine culture, associate and together may contribute to disease pathogenesis. Patients were classified as being infected with Prairie Epidemic ePA (PES) or a non-clonal strain, unique PA strains (uPA), through a retrospective assessment of a comprehensive strain biobank using a combination of PFGE and PES-specific PCR. Patients were matched to age, sex, time-period controls and sputum samples from equivalent time periods were identified from a sputum biobank. Bacterial 16S rRNA gene profiling and Pseudomonas qPCR was used to characterize the respiratory microbiome. We identified 31 patients infected with PES and matched them with uPA controls. Patients infected with PES at baseline have lower microbial diversity (P = 0.02) and higher P. aeruginosa relative abundance (P < 0.005). Microbial community structure was found to cluster by PA strain type, although it was not the main determinant of community structure as additional factors were also found to be drivers of CF community structure. Communities from PES infected individuals were enriched with Pseudomonas, Streptococcus and Prevotella OTUs. The disproportionate disease experienced by ePA infected CF patients may be mediated through a combination of pathogen-pathogen factors as opposed to strictly enhanced virulence of infecting P. aeruginosa strains.

A diverse microbiota exists within the airways of individuals with non-cystic fibrosis bronchiectasis (nCFB). How the lung microbiome evolves over time, and whether changes within the microbiome correlate with future disease progression is not yet known. We assessed the microbial community structure of 133 serial sputa and subsequent disease course of 29 nCFB patients collected over a span of 4–16 years using 16S rRNA paired-end sequencing. Interestingly, no significant shifts in the microbial community of individuals were observed during extended follow-up suggesting the microbiome remains relatively stable over prolonged periods. Samples that were Pseudomonas aeruginosa culture positive displayed markedly different microbial community structures compared to those that were positive for Haemophilus influenzae. Importantly, patients with sputum of lower microbial community diversity were more likely to experience subsequent lung function decline as defined by annual change in ≥−1 FEV1% predicted. Shannon diversity values 1 decline (P = 0.002). However, the relative abundance of particular core microbiota constituents did not associate with risk of decline. Here we present data confirming that the microbiome of nCFB individuals is generally stable, and that microbiome-based measurements may have a prognostic role as biomarkers for nCFB.

Background To improve clinical outcomes, cystic fibrosis (CF) patients with chronic Pseudomonas aeruginosa infections are prescribed inhaled anti-pseudomonal antibiotics. Although, a diverse microbial community exists within CF airways, little is known about how the CF microbiota influences patient outcomes. We hypothesized that organisms within the CF microbiota are affected by inhaled-antibiotics and baseline microbiome may be used to predict therapeutic response. Methods Adults with chronic P. aeruginosa infection from four clinics were observed during a single 28-day on/off inhaled-aztreonam cycle. Patients performed serial sputum collection, CF-respiratory infection symptom scores (CRISS), and spirometry. Patients achieving a decrease of ≥2 CRISS by day 28 were categorized as subjective responders (SR). The airway microbiome was defined by Illumina MiSeq analysis of the 16S rRNA gene. Results Thirty-seven patients (median 37.4 years and FEV1 44% predicted) were enrolled. No significant cohort-wide changes in the microbiome were observed between on/off AZLI cycles in either alpha- or beta-diversity metrics. However, at an individual level shifts were apparent. Twenty-one patients (57%) were SR and fourteen patients did not subjectively respond. While alpha-diversity metrics did not associate with response, patients who did not subjectively respond had a higher abundance of Staphylococcus and Streptococcus, and lower abundance of Haemophilus. Conclusions The CF microbiome is relatively resilient to AZLI perturbations. However, associated changes were observed at the individual patient level. The relative abundance of key “off-target” organisms associated with subjective improvements suggesting that the microbiome may be used as a tool to predict patient response - potentially improving outcomes.

Bacteria possess signal transduction pathways capable of sensing and responding to a wide variety of signals. The Cpx envelope stress response, composed of the sensor histidine kinase CpxA and the response regulator CpxR, senses and mediates adaptation to insults to the bacterial envelope. The Cpx response has been implicated in the regulation of a number of envelope-localized virulence determinants across bacterial species. Here, we show that activation of the Cpx pathway in Vibrio cholerae El Tor strain C6706 leads to a decrease in expression of the major virulence factors in this organism, cholera toxin (CT) and the toxin-coregulated pilus (TCP). Our results indicate that this occurs through the repression of production of the ToxT regulator and an additional upstream transcription factor, TcpP. The effect of the Cpx response on CT and TCP expression is mostly abrogated in a cyclic AMP receptor protein (CRP) mutant, although expression of the crp gene is unaltered. Since TcpP production is controlled by CRP, our data suggest a model whereby the Cpx response affects CRP function, which leads to diminished TcpP, ToxT, CT, and TCP production.

The Cpx pathway, a two-component system that employs the sensor histidine kinase CpxA and the response regulator CpxR, regulates crucial envelope stress responses across bacterial species and affects antibiotic resistance. To characterize the CpxR regulon inVibrio cholerae, the transcriptional profile of the pandemicV. choleraeEl Tor C6706 strain was examined upon overexpression ofcpxR. Our data show that the Cpx regulon ofV. choleraeis enriched in genes encoding membrane-localized and transport proteins, including a large number of genes known or predicted to be iron regulated. Activation of the Cpx pathway further led to the expression of TolC, the major outer membrane pore, and of components of two RND efflux systems inV. cholerae. We show that iron chelation, toxic compounds, or deletion of specific RND efflux components leads to Cpx pathway activation. Furthermore, mutations that eliminate the Cpx response or members of its regulon result in growth phenotypes in the presence of these inducers that, together with Cpx pathway activation, are partially suppressed by iron. Cumulatively, our results suggest that a major function of the Cpx response inV. choleraeis to mediate adaptation to envelope perturbations caused by toxic compounds and the depletion of iron.

The Cpx envelope stress response facilitates adaptation to envelope stresses that lead to the misfolding of periplasmic proteins. Cpx-mediated adaptation involves elevated expression of periplasmic proteases and chaperones. Previously, we demonstrated that induction of the Cpx envelope stress response in enteropathogenic Escherichia coli (EPEC) also results in inhibition of type III secretion (T3S) and that this is correlated with downregulated transcription of the relevant genes. Here, we investigated whether the Cpx stress response might also exert posttranscriptional effects on the T3S apparatus. We show that DsbA is required for T3S, while removal of transcription factor CpxR or the Cpx-regulated folding factor CpxP or PpiA has minimal effects. Conversely, the entire T3S complex is removed from the envelope when the Cpx response is activated. Overexpression of the chaperone/protease DegP mimics the Cpx-dependent inhibition of the T3S complex at a posttranscriptional level, and mutation of degP partly abrogates the ability of the Cpx response to inhibit the T3S complex and motility. We present data that suggest that both the protease and chaperone activities of DegP are likely important for the impact on T3S. Altogether, our data indicate that DegP is normally a part of the Cpx-mediated inhibition of virulence determinant expression in EPEC and that additional factors are involved.

AIM: To investigate Helicobacter pylori (H. pylori) CagA diversity and to evaluate the association between protein polymorphisms and the occurrence of gastric pathologies. METHODS: One hundred and twenty-two clinical isolates of H. pylori cultured from gastric biopsies obtained from Colombian patients with dyspepsia were included as study material. DNA extracted from isolates was used to determine cagA status, amplifying the C-terminal cagA gene region by polymerase chain reaction. One hundred and six strains with a single amplicon were sequenced and results were used to characterize the 3’ variable region of the cagA gene. To establish the number and type of tyrosine phosphorylation motifs Glutamine acid-Proline-Isoleucine-Tyrosine-Alanine (EPIYA) bioinformatic analysis using Amino Acid Sequence Analyzer-Amino Acid Sequence Analyzer software was conducted. Analysis of the association between the number of EPIYA motifs and the gastric pathology was performed using χ2 test and analysis of the presence of EPIYA-C motifs in relation to the pathology was made by logistic regression odds ratios. Comparisons among EPIYA types found and those reported in GenBank were performed using a proportion test in Statistix Analytical Software version 8.0. RESULTS: After amplification of the 3’ of the cagA gene, 106 from 122 isolates presented a single amplicon and 16 showed multiple amplicons. As expected, diversity in the size of the cagA unique fragments among isolates was observed. The 106 strains that presented a single amplicon after 3’ cagA amplification came from patients with gastritis (19 patients), atrophic gastritis (21), intestinal metaplasia (26), duodenal ulcer (22) and gastric cancer. DNA sequence analysis showed that the differences in size of 3’ cagA unique fragments was attributable to the number of EPIYA motifs: 1.9% had two EPIYA motifs, 62.3% had three, 33.0% had four and 2.8% had five motifs. The majority of tested clinical strains (62.3%) were found to harbor the ABC combination of EPIYA motifs and a significant statistical difference was observed between the frequencies of ABCC tyrosine phosphorylation motifs and Western strains sequences deposited in GenBank. CONCLUSION: The present report describes a lack of association between H. pylori CagA-protein polymorphisms and pathogenesis. ABCC high frequency variations compared with Western-strains sequences deposited in GenBank require more investigation.

AIM: To investigate the influence of the CagA diversity in Helicobacter pylori (H. pylori) strains from Colombia on the host cell biology. METHODS: Eighty-four H. pylori-cagA positive strains with different Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs patterns, isolated from patients with gastritis (n = 17), atrophic gastritis (n = 17), duodenal ulcer (n = 16), intestinal metaplasia (n = 16) and gastric cancer (n = 18), were included. To determine the integrity of the cag pathogenicity island (cagPAI) we evaluated the presence of cagA, cagT, cagE, and cag10 genes by polymerase chain reaction. AGS gastric epithelial cells were infected with each strain and assayed for translocation and tyrosine phosphorylation of CagA by western blot, secretion of interleukin-8 (IL-8) by enzyme-linked immuno sorbent assay after taking supernatants from cocultures and cell elongation induction. For cell elongation quantification, coculture photographs were taken and the proportion of “hummingbird” cells (> 15 μm) was determined. RESULTS: Overall 72% (60/84) of the strains were found to harbor a functional cagPAI. Levels of phosphorylated CagA were significantly higher for isolates from duodenal ulcer than the ones in strains from gastritis, atrophic gastritis, intestinal metaplasia and gastric cancer (49.1% ± 23.1% vs 21.1% ± 19.5%, P < 0.02; 49.1% ± 23.1% vs 26.2% ± 14.8%, P < 0.045; 49.1% ± 23.1% vs 21.5% ± 19.5%, P < 0.043 and 49.1% ± 23.1% vs 29.5% ± 27.1%, P < 0.047 respectively). We observed variable IL-8 expression levels ranging from 0 to 810 pg/mL and from 8.8 to 1442 pg/mL at 6 h and 30 h post-infection, respectively. cagPAI-defective strains did not induce detectable levels of IL-8 at 6 h post-infection. At 30 h post-infection all strains induced IL-8 expression in AGS cells, although cagPAI-defective strains induced significantly lower levels of IL-8 than strains with a functional cagPAI (57.1 ± 56.6 pg/mL vs 513.6 ± 338.6 pg/mL, P < 0.0001). We did not observe differences in the extent of cell elongation induction between strains with a functional or a defective cagPAI in 6 h cocultures. At 24 h post infection strains with functional cagPAI showed high diversity in the extent of hummingbird phenotype induction ranging from 7% to 34%. cagPAI defective strains induced significantly lower levels of elongation than strains with functional cagPAI with one or more than one EPIYA-C motif (15.1% ± 5.2% vs 18.9% ± 4.7%, P < 0.03; and 15.1% ± 5.2% vs 20.0% ± 5.1%, P < 0.003 respectively). No differences were observed in cellular elongation induction or IL-8 expression among H. pylori strains bearing one and more than one EPIYA-C motifs, neither at 6 h nor at 24 h of coculture. There were no associations between the levels of induction of cell elongation or IL-8 expression and number of EPIYA motifs or pathology. CONCLUSION: The present work describes a lack of association between H. pylori CagA protein EPIYA motifs variations from Colombian isolates and disease-associated cellular responses.