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Goshia, T.

Publications and source records attributed to Goshia, T..

2 recordsLinked to original sources

Selection-free whole genome transplantation revives dead microbes

We present a living, synthetic bacterial cell made by transplanting a complete genome into a dead cell. After killing Mycoplasma capricolum cells by chemically crosslinking their genome with Mitomycin C (MMC), we installed synthetic Mycoplasma mycoides genomes into the resulting dead cells using Whole Genome Transplantation (WGT)1,2. During WGT, a synthetic donor genome is placed into a recipient cell, thereby reprogramming that cell to adopt a new genetic identity3. WGT has only been demonstrated using species within one phylogenetic clade of Mollicutes bacteria4. A major barrier to expanding WGT to diverse bacterial species has been the inability to inactivate the recipient genome, leading to false positive transplants due to homologous recombination of antibiotic resistance markers from the donor genome into the recipient cell genome. Here, we address this key limitation by removing reliance on an antibiotic resistance marker to select for transplants; recipient cells are dead unless revived by the installation of a new genome. Our work demonstrates a general approach to fully inactivate the recipient cell genome, reports the first living synthetic bacterial cell constructed from non-living parts, and advances WGT for building engineered or synthetic cells for diverse applications.

synthetic biology↗

Universal Digital High Resolution Melt for the detection of pulmonary mold infections

BackgroundInvasive mold infections (IMIs) such as aspergillosis, mucormycosis, fusariosis, and lomentosporiosis are associated with high morbidity and mortality, particularly in immunocompromised patients, with mortality rates as high as 40% to 80%. Outcomes could be substantially improved with early initiation of appropriate antifungal therapy, yet early diagnosis remains difficult to establish and often requires multidisciplinary teams evaluating clinical and radiological findings plus supportive mycological findings. Universal digital high resolution melting analysis (U-dHRM) may enable rapid and robust diagnosis of IMI. This technology aims to accomplish timely pathogen detection at the single genome level by conducting broad-based amplification of microbial barcoding genes in a digital polymerase chain reaction (dPCR) format, followed by high-resolution melting of the DNA amplicons in each digital reaction to generate organism-specific melt curve signatures that are identified by machine learning. MethodsA universal fungal assay was developed for U-dHRM and used to generate a database of melt curve signatures for 19 clinically relevant fungal pathogens. A machine learning algorithm (ML) was trained to automatically classify these 19 fungal melt curves and detect novel melt curves. Performance was assessed on 73 clinical bronchoalveolar lavage (BAL) samples from patients suspected of IMI. Novel curves were identified by micropipetting U-dHRM reactions and Sanger sequencing amplicons. ResultsU-dHRM achieved an average of 97% fungal organism identification accuracy and a turn-around-time of 4hrs. Pathogenic molds (Aspergillus, Mucorales, Lomentospora and Fusarium) were detected by U-dHRM in 73% of BALF samples suspected of IMI. Mixtures of pathogenic molds were detected in 19%. U-dHRM demonstrated good sensitivity for IMI, as defined by current diagnostic criteria, when clinical findings were also considered. ConclusionsU-dHRM showed promising performance as a separate or combination diagnostic approach to standard mycological tests. The speed of U-dHRM and its ability to simultaneously identify and quantify clinically relevant mold pathogens in polymicrobial samples as well as detect emerging opportunistic pathogens may provide information that could aid in treatment decisions and improve patient outcomes.

microbiology↗