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Zaiko, A.

Publications and source records attributed to Zaiko, A..

2 recordsLinked to original sources

Molecular methods reveal responses of bacterial communities, including indicator species, to ballast water management

Ballast water (BW) is an important vector for the global translocation of bacterial taxa, including pathogens. Legal frameworks establishing limits on the discharge of live organisms into recipient environments have been designed to reduce risks of microbial invasions, and understanding the impacts of BW management on bacterial communities is critical for assessing the effectiveness of these practices. Here we evaluate changes in bacterial communities associated with both BW treatment (BWT) and a combined management approach of BWT plus BW exchange (BWT+E). Samples were collected on two experimental voyages designed specifically to compare BW-associated biota before and after management. Microbial community structure and inferred function were assessed based on high throughput sequencing of 16S rRNA amplicons, and bacterial indicator taxa E. coli and enterococci were analyzed using targeted qPCR. As expected, both BWT alone and BWT+E dramatically changed bacterial communities, with the latter resulting in the largest overall decreases in bacterial diversity. Increases in Gammaproteobacteria, especially in the genus Pseudomonas, were particularly notable, with concomitant decreases in Alphaproteobacteria and Bacteroidia. Shifts in predicted bacterial function associated with BWT were similar for both voyages, despite significant differences in community structure, and may represent selection for r-strategists capable of active regrowth after BWT. qPCR estimates of indicator taxa were similar to those obtained through standard culture methods but may offer increased sensitivity for detecting changes associated with management. Our results indicate that BW management is effective at reducing bacterial communities but suggest that further research is needed to understand risks associated with taxa that may survive BWT.

ecology↗

CRISPR-based environmental biosurveillance assisted via artificial intelligence design of guide-RNAs

Environmental biosecurity challenges are worsening for aquatic ecosystems as climate change and increased anthropogenic pressures facilitate the spread of invasive species, thereby broadly impacting ecosystem composition, functioning, and services. Environmental DNA (eDNA) has transformed traditional biomonitoring through detection of trace DNA fragments left by organisms in their surroundings, primarily by application of the quantitative polymerase chain reaction (qPCR). However, qPCR presents challenges, including limited portability, reliance on precise thermal cycling, and susceptibility to inhibitors. To address these challenges and enable field-deployable monitoring, isothermal amplification techniques such as Recombinase Polymerase Amplification (RPA) paired with Clustered Regularly Interspaced Short Palindromic Repeats and associated proteins (CRISPR-Cas) have been proposed as alternatives. We report here the development of CORSAIR (CRISPR-based envirOnmental biosuRveillance aSsisted via Artificial Intelligence guide-RNAs), that harnesses the programmability of the CRISPR-Cas technology, RPA and the artificial intelligence (AI)-based tool Activity-informed Design with All-inclusive Patrolling of Targets (ADAPT) to deploy a swift RPA-CRISPR-Cas13a-based method that detects eDNA from two invasive species as proof of concept: Sabella spallanzanii and Undaria pinnatifida. CORSAIR showcased a robust, streamlined method augmented by ADAPT, reaching a high specificity when tested against co-occurring species and a 100% agreement with 12 PCR-benchmarked eDNA samples, reaching a sensitivity of 0.34 copies uL-1 in 1 hour with a cost of 3.5 USD per sample; thus highlighting CORSAIR as a powerful environmental biosurveillance platform for environmental nucleic acid detection. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/627849v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@b60942org.highwire.dtl.DTLVardef@119e924org.highwire.dtl.DTLVardef@1956bforg.highwire.dtl.DTLVardef@18e18b9_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

molecular biology↗