We have described multipotent progenitor-like cells within the major pancreatic ducts (MPDs) of the human pancreas. They express PDX1, its surrogate surface marker P2RY1, and the bone morphogenetic protein (BMP) receptor 1A (BMPR1A)/activin-like kinase 3 (ALK3), but not carbonic anhydrase II (CAII). Here we report the single-cell RNA sequencing (scRNA-seq) of ALK3 ^bright+ -sorted ductal cells, a fraction that harbors BMP-responsive progenitor-like cells. Our analysis unveiled the existence of multiple subpopulations along two major axes, one that encompasses a gradient of ductal cell differentiation stages, and another featuring cells with transitional phenotypes toward acinar tissue. A third potential ducto-endocrine axis is revealed upon integration of the ALK3 ^bright+ dataset with a single-cell whole-pancreas transcriptome. When transplanted into immunodeficient mice, P2RY1 ⁺ /ALK3 ^bright+ populations (enriched in PDX1 ⁺ /ALK3 ⁺ /CAII ⁻ cells) differentiate into all pancreatic lineages, including functional β-cells. This process is accelerated when hosts are treated systemically with an ALK3 agonist. We found PDX1 ⁺ /ALK3 ⁺ /CAII ⁻ progenitor-like cells in the MPDs of types 1 and 2 diabetes donors, regardless of the duration of the disease. Our findings open the door to the pharmacological activation of progenitor cells in situ.

A phenomenon of genetic compensation is commonly observed when an organism with a disease-bearing mutation shows incomplete penetrance of the disease phenotype. Such incomplete phenotypic penetrance, or genetic compensation, is more commonly found in stable knockout models, rather than transient knockdown models. As such, these incidents present a challenge for the disease modeling field, although a deeper understanding of genetic compensation may also hold the key for novel therapeutic interventions. In our study we created a knockout model of slc25a46 gene, which is a recently discovered important player in mitochondrial dynamics, and deleterious mutations in which are known to cause peripheral neuropathy, optic atrophy and cerebellar ataxia. We report a case of genetic compensation in a stable slc25a46 homozygous zebrafish mutant (hereafter referred as “mutant”), in contrast to a penetrant disease phenotype in the first generation (F0) slc25a46 mosaic mutant (hereafter referred as “crispant”), generated with CRISPR/Cas-9 technology. We show that the crispant phenotype is specific and rescuable. By performing mRNA sequencing, we define significant changes in slc25a46 mutant’s gene expression profile, which are largely absent in crispants. We find that among the most significantly altered mRNAs, anxa6 gene stands out as a functionally relevant player in mitochondrial dynamics. We also find that our genetic compensation case does not arise from mechanisms driven by mutant mRNA decay. Our study contributes to the growing evidence of the genetic compensation phenomenon and presents novel insights about Slc25a46 function. Furthermore, our study provides the evidence for the efficiency of F0 CRISPR screens for disease candidate genes, which may be used to advance the field of functional genetics.

Background: Influenza virus is responsible for a yearly epidemic in much of the world. To better predict short-term, seasonal variations in flu infection rates and possible mechanisms of yearly infection variation, we trained a Long Short-Term Memory (LSTM)-based deep neural network on historical Influenza-Like-Illness (ILI), climate, and population data. Methods: Data were collected from the Centers for Disease Control and Prevention (CDC), the National Center for Environmental Information (NCEI), and the United States Census Bureau. The model was initially built in Python using the Keras API and tuned manually. We explored the roles of temperature, precipitation, local wind speed, population size, vaccination rate, and vaccination efficacy. The model was validated using K-fold cross validation as well as forward chaining cross validation and compared to several standard algorithms. Finally, simulation data was generated in R and used for further exploration of the model. Results: We found that temperature is the strongest predictor of ILI rates, but also found that precipitation increased the predictive power of the network. Additionally, the proposed model achieved a +1 week prediction mean absolute error (MAE) of 0.1973. This is less than half of the MAE achieved by the next best performing algorithm. Additionally, the model accurately predicted simulation data. To test the role of temperature in the network, we phase-shifted temperature in time and found a predictable reduction in prediction accuracy. Conclusions: The results of this study suggest that short term flu forecasting may be effectively accomplished using architectures traditionally reserved for time series analysis. The proposed LSTM-based model was able to outperform comparison models at the +1 week time point. Additionally, this model provided insight into the week-to-week effects of climatic and biotic factors and revealed potential patterns in data series. Specifically, we found that temperature is the strongest predictor of seasonal flu infection rates. This information may prove to be especially important for flu forecasting given the uncertain long-term impact of the SARS-CoV-2 pandemic on seasonal influenza.

As a dioxygenase, Ten-Eleven Translocation 2 (TET2) catalyzes subsequent steps of 5-methylcytosine (5mC) oxidation. TET2 plays a critical role in the self-renewal, proliferation, and differentiation of hematopoietic stem cells, but its impact on mature hematopoietic cells is not well-characterized. Here we show that Tet2 plays an essential role in osteoclastogenesis. Deletion of Tet2 impairs the differentiation of osteoclast precursor cells (macrophages) and their maturation into bone-resorbing osteoclasts in vitro. Furthermore, Tet2−/− mice exhibit mild osteopetrosis, accompanied by decreased number of osteoclasts in vivo. Tet2 loss in macrophages results in the altered expression of a set of genes implicated in osteoclast differentiation, such as Cebpa, Mafb, and Nfkbiz. Tet2 deletion also leads to a genome-wide alteration in the level of 5-hydroxymethylcytosine (5hmC) and altered expression of a specific subset of macrophage genes associated with osteoclast differentiation. Furthermore, Tet2 interacts with Runx1 and negatively modulates its transcriptional activity. Our studies demonstrate a novel molecular mechanism controlling osteoclast differentiation and function by Tet2, that is, through interactions with Runx1 and the maintenance of genomic 5hmC. Targeting Tet2 and its pathway could be a potential therapeutic strategy for the prevention and treatment of abnormal bone mass caused by the deregulation of osteoclast activities.

Peripheral mechanoreceptor-based treatments such as acupuncture and chiropractic manipulation have shown success in modulating the mesolimbic dopamine (DA) system originating in the ventral tegmental area (VTA) of the midbrain and projecting to the nucleus accumbens (NAc) of the striatum. We have previously shown that mechanoreceptor activation via whole-body vibration (WBV) ameliorates neuronal and behavioral effects of chronic ethanol exposure. In this study, we employ a similar paradigm to assess the efficacy of WBV as a preventative measure of neuronal and behavioral effects of morphine withdrawal in a Wistar rat model. We demonstrate that concurrent administration of WBV at 80 Hz with morphine over a 5-day period significantly reduced adaptations in VTA GABA neuronal activity and NAc DA release and modulated expression of δ-opioid receptors (DORs) on NAc cholinergic interneurons (CINs) during withdrawal. We also observed a reduction in behavior typically associated with opioid withdrawal. WBV represents a promising adjunct to current intervention for opioid use disorder (OUD) and should be examined translationally in humans.