Drop it all: extraction-free detection of targeted marine species through optimized direct droplet digital PCR.

Molecular biomonitoring programs increasingly use environmental DNA (eDNA) for detecting targeted species such as marine non-indigenous species (NIS) or endangered species. However, the current molecular detection workflow is cumbersome and time-demanding, and thereby can hinder management efforts and restrict the "opportunity window" for rapid management responses. Here, we describe a direct droplet digital PCR (direct-ddPCR) approach to detect species-specific free-floating extra-cellular eDNA (free-eDNA) signals, i.e., detection of species-specific eDNA without the need for filtration or DNA extraction, with seawater samples. This first proof-of-concept aquarium study was conducted with three distinct marine species: the Mediterranean fanworm Sabella spallanzanii, the ascidian clubbed tunicate Styela clava, and the brown bryozoan Bugula neritina to evaluate the detectability of free-eDNA in seawater. The detectability of targeted free-eDNA was assessed by directly analysing aquarium marine water samples using an optimized species-specific ddPCR assay. The results demonstrated the consistent detection of S. spallanzanii and B. neritina free-eDNA when these organisms were present in high abundance. Once organisms were removed, the free-eDNA signal exponentially declined, noting that free-eDNA persisted between 24-72 h. Results indicate that organism biomass, specimen characteristics (e.g., stress and viability), and species-specific biological differences may influence free-eDNA detectability. This study represents the first step in assessing the feasibility of direct-ddPCR technology for the detection of marine species. Our results provide information that could aid in the development of new technology, such as a field development of ddPCR systems, which could allow for automated continuous monitoring of targeted marine species, enabling point-of-need detection and rapid management responses.

CRISPR-Cas-Based Biomonitoring for Marine Environments: Toward CRISPR RNA Design Optimization Via Deep Learning.

Almost all of Earth's oceans are now impacted by multiple anthropogenic stressors, including the spread of nonindigenous species, harmful algal blooms, and pathogens. Early detection is critical to manage these stressors effectively and to protect marine systems and the ecosystem services they provide. Molecular tools have emerged as a promising solution for marine biomonitoring. One of the latest advancements involves utilizing CRISPR-Cas technology to build programmable, rapid, ultrasensitive, and specific diagnostics. CRISPR-based diagnostics (CRISPR-Dx) has the potential to allow robust, reliable, and cost-effective biomonitoring in near real time. However, several challenges must be overcome before CRISPR-Dx can be established as a mainstream tool for marine biomonitoring. A critical unmet challenge is the need to design, optimize, and experimentally validate CRISPR-Dx assays. Artificial intelligence has recently been presented as a potential approach to tackle this challenge. This perspective synthesizes recent advances in CRISPR-Dx and machine learning modeling approaches, showcasing CRISPR-Dx potential to progress as a rising molecular tool candidate for marine biomonitoring applications.

Pest Alert Tool-a web-based application for flagging species of concern in metabarcoding datasets.

Advances in high-throughput sequencing (HTS) technologies and their increasing affordability have fueled environmental DNA (eDNA) metabarcoding data generation from freshwater, marine and terrestrial ecosystems. Research institutions worldwide progressively employ HTS for biodiversity assessments, new species discovery and ecological trend monitoring. Moreover, even non-scientists can now collect an eDNA sample, send it to a specialized laboratory for analysis and receive in-depth biodiversity record from a sampling site. This offers unprecedented opportunities for biodiversity assessments across wide temporal and spatial scales. The large volume of data produced by metabarcoding also enables incidental detection of species of concern, including non-indigenous and pathogenic organisms. We introduce an online app-Pest Alert Tool-for screening nuclear small subunit 18S ribosomal RNA and mitochondrial cytochrome oxidase subunit I datasets for marine non-indigenous species as well as unwanted and notifiable marine organisms in New Zealand. The output can be filtered by minimum length of the query sequence and identity match. For putative matches, a phylogenetic tree can be generated through the National Center for Biotechnology Information's BLAST Tree View tool, allowing for additional verification of the species of concern detection. The Pest Alert Tool is publicly available at https://pest-alert-tool-prod.azurewebsites.net/.

A Unique Morphological Phenotype in Chemoresistant Triple-Negative Breast Cancer Reveals Metabolic Reprogramming and PLIN4 Expression as a Molecular Vulnerability.

The major obstacle in successfully treating triple-negative breast cancer (TNBC) is resistance to cytotoxic chemotherapy, the mainstay of treatment in this disease. Previous preclinical models of chemoresistance in TNBC have suffered from a lack of clinical relevance. Using a single high dose chemotherapy treatment, we developed a novel MDA-MB-436 cell-based model of chemoresistance characterized by a unique and complex morphologic phenotype, which consists of polyploid giant cancer cells giving rise to neuron-like mononuclear daughter cells filled with smaller but functional mitochondria and numerous lipid droplets. This resistant phenotype is associated with metabolic reprogramming with a shift to a greater dependence on fatty acids and oxidative phosphorylation. We validated both the molecular and histologic features of this model in a clinical cohort of primary chemoresistant TNBCs and identified several metabolic vulnerabilities including a dependence on PLIN4, a perilipin coating the observed lipid droplets, expressed both in the TNBC-resistant cells and clinical chemoresistant tumors treated with neoadjuvant doxorubicin-based chemotherapy. These findings thus reveal a novel mechanism of chemotherapy resistance that has therapeutic implications in the treatment of drug-resistant cancer. IMPLICATIONS: These findings underlie the importance of a novel morphologic-metabolic phenotype associated with chemotherapy resistance in TNBC, and bring to light novel therapeutic targets resulting from vulnerabilities in this phenotype, including the expression of PLIN4 essential for stabilizing lipid droplets in resistant cells.