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Biology subjects

Abo, K.

Publications and source records attributed to Abo, K..

3 recordsLinked to original sources

AT2-intrinsic Z-AAT expression drives conserved inflammatory and proteotoxic stress responses and predisposes to emphysema

Individuals homozygous for the SERPINA1 "Z" mutation with alpha-1 antitrypsin deficiency (AATD) are highly susceptible to emphysema. This predisposition has classically been attributed to a relative deficiency of circulating alpha-1 antitrypsin (AAT) reaching the lungs and associated protease-antiprotease imbalance. Accumulating evidence suggests that the presence of misfolded Z-AAT protein either in the circulation, the lung interstitium, or within resident lung cells could contribute to emphysema pathogenesis. We have shown that type 2 alveolar epithelial cells (AT2s), progenitor cells of the lung alveolus, heterogeneously retain Z-AAT and exhibit a transcriptional disease signature in AATD patient samples. However, a lack of model systems that faithfully recapitulate AT2 biology and associated Z-AAT expression has limited our ability to study this phenomenon. Here, we apply syngeneic induced pluripotent stem cell-derived AT2s (iAT2s) and a novel mouse model featuring AT2-specific inducible human SERPINA1 expression to interrogate the cell-instrinsic consequences of Z-AAT expression, validating findings in an independent dataset of human COPD lung tissue comparing ZZ to MM SERPINA1 genotypes. We find further evidence of Z-AAT retention within AT2s and identify shared AT2 transcriptomic disease signatures conserved across model systems, characterized by innate immune and inflammatory signaling, NF-{kappa}B activation, and endoplasmic reticulum stress. Mice with AT2-specific Z-AAT expression additionally demonstrate increased susceptibility to elastase-induced emphysema, providing functional evidence for AT2-intrinsic contributions to AATD-associated lung disease. Within iAT2s, a subpopulation of Z-AAT expressing cells exhibits activation of the PERK-eIF2 signaling axis and markers of an alveolar basal intermediate (ABI) state, emerging cell-autonomously in the absence of mesenchymal co-culture.Together, these data provide evidence that Z-AAT expression in AT2s induces heterogenous cell-intrinsic stress responses including proteotoxic stress, inflammatory signaling, and aberrant cell fate adoption, and is sufficient to result in predisposition to injury, supporting a potential contribution of AT2-intrinsic Z-AAT toxicity to human AATD-associated emphysema pathogenesis.

cell biology↗

Human airway lineages derived from pluripotent stem cells reveal the epithelial responses to SARS-CoV-2 infection

There is an urgent need to understand how SARS-CoV-2 infects the airway epithelium and in a subset of individuals leads to severe illness or death. Induced pluripotent stem cells (iPSCs) provide a near limitless supply of human cells that can be differentiated into cell types of interest, including airway epithelium, for disease modeling. We present a human iPSC-derived airway epithelial platform, composed of the major airway epithelial cell types, that is permissive to SARS-CoV-2 infection. Subsets of iPSC-airway cells express the SARS-CoV-2 entry factors ACE2 and TMPRSS2. Multiciliated cells are the primary initial target of SARS-CoV-2 infection. Upon infection with SARS-CoV-2, iPSC-airway cells generate robust interferon and inflammatory responses and treatment with remdesivir or camostat methylate causes a decrease in viral propagation and entry, respectively. In conclusion, iPSC-derived airway cells provide a physiologically relevant in vitro model system to interrogate the pathogenesis of, and develop treatment strategies for, COVID-19 pneumonia. Highlights and eTOC blurbO_LISubsets of human iPSC-airway epithelial cells express SARS-Co-V entry factors ACE2 and TMPRSS2. C_LIO_LIiPSC-airway cells are permissive to SARS-CoV-2 infection via multiciliated cells. C_LIO_LISARS-CoV-2 infection of iPSC-airway leads to a robust interferon and inflammatory response. C_LIO_LIiPSC-airway is a physiologically relevant model to study SARS-CoV-2 infection. C_LI

cell biology↗

National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the \"first 90\" from program and survey data

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSObjectiveC_ST_ABSHIV testing services (HTS) are a crucial component of national HIV responses. Learning ones HIV diagnosis is the entry point to accessing life-saving antiretroviral treatment and care. Recognizing the critical role of HTS, the Joint United Nations Programme on HIV/AIDS (UNAIDS) launched the 90-90-90 targets stipulating that by 2020, 90% of people living with HIV know their status, 90% of those who know their status receive antiretroviral therapy, and 90% of those on treatment have a suppressed viral load. Countries will need to regularly monitor progress on these three indicators. Estimating the proportion of people living with HIV who know their status (i.e., the "first 90"), however, is difficult. MethodsWe developed a mathematical model (henceforth referred to as "F90") that formally synthesizes population-based survey and HTS program data to estimate HIV status awareness over time. The proposed model uses country-specific HIV epidemic parameters from the standard UNAIDS Spectrum model to produce outputs that are consistent with other national HIV estimates. The F90 model provides estimates of HIV testing history, diagnosis rates, and knowledge of HIV status by age and sex. We validate the F90 model using both in-sample comparisons and out-of-sample predictions using data from three countries: Cote dIvoire, Malawi, and Mozambique. ResultsIn-sample comparisons suggest that the F90 model can accurately reproduce longitudinal sex-specific trends in HIV testing. Out-of-sample predictions of the fraction of PLHIV ever tested over a 4-to-6-year time horizon are also in good agreement with empirical survey estimates. Importantly, out-of-sample predictions of HIV knowledge are consistent (i.e., within 4% points) with those of the fully calibrated model in the three countries, when HTS program data are included. The F90 models predictions of knowledge of status are higher than available self-reported HIV awareness estimates, however, suggesting -in line with previous studies- that these self-reports are affected by non-disclosure of HIV status awareness. ConclusionKnowledge of HIV status is a key indicator to monitor progress, identify bottlenecks, and target HIV responses. The F90 model can help countries track progress towards their "first 90" by leveraging surveys of HIV testing behaviors and annual HTS program data.

epidemiology↗