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Multidrug-resistant bacteria are of critical importance and a problem for human health and food preservation; the discovery of new antimicrobial substances to control their proliferation is part of the solution. This work reports on 57 antagonistic Aeromonas strains, of which 38 strains were antagonistic towards problematic human pathogens. The genome of the most antagonistic strain was sequenced and identified as Aeromonas allosaccharophila. Its genome was fully annotated and mined for genes that might explain that activity. Strain AE59-TE was antagonistic toward clinically relevant gram-negative and gram-positive multidrug-resistant bacteria, including Klebsiella pneumoniae KPC, Escherichia coli ESBL, Salmonella typhimurium, and Staphylococcus aureus MRSA. Strain AE59-TE2 was identified by multilocus sequence analysis. Genome mining identified four genes homologous to the bacteriocin, zoocin A from Streptococcus equi and a gene 98% similar to cvpA linked to colicin V production. A. allosaccharophila strain AE59-TE2 produced antimicrobial activity against a broad range of bacteria, including important gram-negative bacteria, not typically targeted by bacteriocins. Herewere described novel zoocin genes that are promising for industrial applications in the food and health sectors. Interesting and important antagonistic activity is described combined with the first detailed genomic analysis of the species Aeromonas allosaccharophila.

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

Interactions between keratinocytes and fibroblasts in the skin layers are crucial in normal tissue development, wound healing, and scarring. This study has investigated the role of keloid keratinocytes in regulating collagen production by primary fibroblasts in vitro. Keloid cells were obtained from removed patients’ tissue whereas normal skin cells were discarded tissue obtained from elective surgery procedures. Fibroblasts and keratinocytes were isolated, cultured, and a transwell co-culture system were used to investigate the effect of keratinocytes on collagen production using a ‘scar-in-a-jar’ model. Keloid fibroblasts produced significantly more collagen than normal skin fibroblasts in monoculture at the RNA, secreted protein, and stable fibrillar protein level. When keloid keratinocytes were added to normal skin fibroblasts, expression of collagen was significantly upregulated in most samples, but when added to keloid fibroblasts, collagen I production was significantly reduced. Interestingly, keloid keratinocytes appear to decrease collagen production by keloid fibroblasts. This suggests that signaling in both keratinocytes and fibroblasts is disrupted in keloid pathology.

As a part of an abnormal healing process of dermal injuries and irritation, keloid scars arise on the skin as benign fibroproliferative tumors. Although the etiology of keloid scarring remains unsettled, considerable recent evidence suggested that keloidogenesis may be driven by epigenetic changes, particularly, DNA methylation. Therefore, genome-wide scanning of methylated cytosine-phosphoguanine (CpG) sites in extracted DNA from 12 keloid scar fibroblasts (KF) and 12 control skin fibroblasts (CF) (six normal skin fibroblasts and six normotrophic fibroblasts) was conducted using the Illumina Human Methylation 450K BeadChip in two replicates for each sample. Comparing KF and CF used a Linear Models for Microarray Data (Limma) model revealed 100,000 differentially methylated (DM) CpG sites, 20,695 of which were found to be hypomethylated and 79,305 were hypermethylated. The top DM CpG sites were associated with TNKS2, FAM45B, LOC723972, GAS7, RHBDD2 and CAMKK1. Subsequently, the most functionally enriched genes with the top 100 DM CpG sites were significantly (p ≤ 0.05) associated with SH2 domain binding, regulation of transcription, DNA-templated, nucleus, positive regulation of protein targeting to mitochondrion, nucleoplasm, Swr1 complex, histone exchange, and cellular response to organic substance. In addition, NLK, CAMKK1, LPAR2, CASP1, and NHS showed to be the most common regulators in the signaling network analysis. Taken together, these findings shed light on the methylation status of keloids that could be implicated in the underlying mechanism of keloid scars formation and remission.

The primary envelopment/de-envelopment of Herpes viruses during nuclear exit is poorly understood. In Herpes simplex virus type-1 (HSV-1), proteins pUL31 and pUL34 are critical, while pUS3 and some others contribute; however, efficient membrane fusion may require additional host proteins. We postulated that vesicle fusion proteins present in the nuclear envelope might facilitate primary envelopment and/or de-envelopment fusion with the outer nuclear membrane. Indeed, a subpopulation of vesicle-associated membrane protein-associated protein B (VAPB), a known vesicle trafficking protein, was present in the nuclear membrane co-locating with pUL34. VAPB knockdown significantly reduced both cell-associated and supernatant virus titers. Moreover, VAPB depletion reduced cytoplasmic accumulation of virus particles and increased levels of nuclear encapsidated viral DNA. These results suggest that VAPB is an important player in the exit of primary enveloped HSV-1 virions from the nucleus. Importantly, VAPB knockdown did not alter pUL34, calnexin or GM-130 localization during infection, arguing against an indirect effect of VAPB on cellular vesicles and trafficking. Immunogold-labelling electron microscopy confirmed VAPB presence in nuclear membranes and moreover associated with primary enveloped HSV-1 particles. These data suggest that VAPB could be a cellular component of a complex that facilitates UL31/UL34/US3-mediated HSV-1 nuclear egress.

Prompt and accurate diagnosis of Nocardia skin infections is important in immunocompromised hosts, especially transplant patients. The sporotrichoid form, which is otherwise known as the lymphocutaneous form of Nocardia skin involvement, can mimic other conditions, including those caused by fungi, mycobacteria, spirochetes, parasites and other bacteria. Delayed or inaccurate diagnosis and treatment of Nocardia skin infections in transplant patients could lead to dissemination of disease and other poor outcomes. Nocardia brasiliensis is a rare cause of lymphocutaneous nocardiosis in solid organ transplant patients with only two other cases reported to our knowledge. This case describes a middle-aged man, who presented 16 years post kidney transplant. He developed a sporotrichoid lesion on his upper extremity one week after gardening. Ultrasound showed a 35-cm abscess tract on his forearm, which was subsequently drained. Nocardia brasiliensis was isolated from pus culture and he was treated successfully with amoxicillin/clavulanate for 6 months. A review of the relevant literature is included.