The pre-Columbian Huecoid and Saladoid cultures were agricultural ethnic groups that supplemented their diets by fishing, hunting and scavenging. Archaeological deposits associated to these cultures contained a variety of faunal osseous remains that hinted at the cultures’ diets. The present study identified zoonotic parasites that may have infected these two cultures as a result of their diets. We used metagenomic sequencing and microscopy data from 540–1,400 year old coprolites as well as the zooarchaeological data to recreate the possible interactions between zoonotic parasites and their hosts. Microscopy revealed Diphyllobothrium spp. and Dipylidium caninum eggs along with unidentified cestode and trematode eggs. DNA sequencing together with functional prediction and phylogenetic inference identified reads of Cryptosporidium spp., Giardia intestinalis and Schistosoma spp. The complimentary nature of the molecular, microscopy and zooarchaeology data provided additional insight into the detected zoonotic parasites’ potential host range. Network modeling revealed that rodents and canids living in close proximity to these cultures were most likely the main source of these zoonotic parasite infections. This communication includes a descriptive analysis of zoonotic parasites infecting Caribbean pre-Columbian cultures in Vieques and network modeling of parasite-host interaction. Our conclusions were based on microscopy and DNA reads extracted from approximately 1,400 to 540 year-old coprolites (un-calibrated years before present). Age and exposure to taphonomic conditions most likely caused the degradation of a portion of the organic material preserved in the coprolites, including parasite eggs, cysts and genetic material. In this study, singleton parasite reads were detected in the metagenomic data. This was likely the outcome of various factors. For instance, non-targeted metagenomic sequencing mainly obtains reads from abundant organisms within the sample, and in the case of fecal metagenomic datasets, these are commonly overpowered by high numbers of bacterial cells. In addition to small amounts of detectable parasite DNA in the feces, ancient DNA damage causes difficulty during sequencing and subsequent alignment of reads to an extant reference sequence. This along with limited representation of parasite genomes in curated reference databases limits the prediction of parasite homologue reads [1]. Furthermore, although contamination and sequencing errors are also a possibility, we believe that this is not the case as precautions were taken to avoid contamination with extant DNA. To overcome these challenges, we performed phylogenetic inference of predicted amino acid homologues to obtain as close as possible to an accurate taxonomic identification. To complement the inherent limitations of the analyses, some of the conclusions presented in this article include intellectual assumptions by the authors based on established knowledge of the field after analyzing and discussing the data.

The respiratory tract has a resident microbiome with low biomass and limited diversity. This results in difficulties with sample preparation for sequencing due to uneven bacteria-to-host DNA ratio, especially for small tissue samples such as mouse lungs. We compared effectiveness of current procedures used for DNA extraction in microbiome studies. Bronchoalveolar lavage fluid (BALF) and lung tissue samples were collected to test different forms of sample pre-treatment and extraction methods to increase bacterial DNA yield and optimize library preparation. DNA extraction using a pre-treatment method of mechanical lysis (lung tissue) and one-step centrifugation (BALF) increased DNA yield and bacterial content of samples. In contrast, a significant increase of environmental contamination was detected after phenol chloroform isoamyl alcohol (PCI) extraction and nested PCR. While PCI has been a standard procedure used in microbiome studies, our data suggests that it is not efficient for DNA extraction of frozen low biomass samples. Finally, a DNA Enrichment kit was tested and found to improve the 16S copy number of lung tissue with a minor shift in microbial composition. Overall, we present a standardized method to provide high yielding DNA and improve sequencing coverage of low microbial biomass frozen samples with minimal contamination.

Adverse cardiac events are a common complication of viral and bacterial pneumonia. For over a century, it has been recognized that influenza infection promotes severe forms of pulmonary disease mainly caused by the bacterium Streptococcus pneumoniae .

Background/Objectives: Breast cancer is diagnosed in 2.3 million women each year and kills 685,000 (~30% of patients) worldwide. The prognosis for many breast cancer subtypes has improved due to treatments targeting the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). In contrast, patients with triple-negative breast cancer (TNBC) tumors, which lack all three commonly targeted membrane markers, more frequently relapse and have lower survival rates due to a lack of tumor-selective TNBC treatments. We aim to investigate TNBC mechanistic markers that could be targeted for treatment. Methods: We performed a secondary TNBC analysis of 196 samples across 10 publicly available bulk RNA-sequencing studies to better understand the molecular mechanism(s) of disease and predict robust mechanistic markers that could be used to improve the mechanistic understanding of and diagnostic capabilities for TNBC. Results: Our analysis identified ~12,500 significant differentially expressed genes (FDR-adjusted p-value < 0.05), including KIF14 and ELMOD3, and two significantly modulated pathways. Additionally, our novel findings include highly accurate mechanistic markers identified using machine learning methods, including CIDEC (97.1% accuracy alone), CD300LG, ASPM, and RGS1 (98.9% combined accuracy), as well as TNBC subtype-differentiating mechanistic markers, including the targets PDE3B, CFD, IFNG, and ADM, which have associated therapeutics that can potentially be repurposed to improve treatment options. We then experimentally and computationally validated a subset of these findings. Conclusions: The results of our analyses can be used to better understand the mechanism(s) of disease and contribute to the development of improved diagnostics and/or treatments for TNBC.