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Phytopathogenic bacteria play important roles in plant productivity, and developments in gene editing have potential for enhancing the genetic tools for the identification of critical genes in the pathogenesis process. CRISPR-based genome editing variants have been developed for a wide range of applications in eukaryotes and prokaryotes. However, the unique mechanisms of different hosts restrict the wide adaptation for specific applications. Here, CRISPR-dCas9 (dead Cas9) and nCas9 (Cas9 nickase) deaminase vectors were developed for a broad range of phytopathogenic bacteria. A gene for a dCas9 or nCas9, cytosine deaminase CDA1, and glycosylase inhibitor fusion protein (cytosine base editor, or CBE) was applied to base editing under the control of different promoters. Results showed that the RecA promoter led to nearly 100% modification of the target region. When residing on the broad host range plasmid pHM1, CBE_RecApis efficient in creating base edits in strains ofXanthomonas,Pseudomonas,ErwiniaandAgrobacterium. CBE based on nCas9 extended the editing window and produced a significantly higher editing rate inPseudomonas. Strains with nonsynonymous mutations in test genes displayed expected phenotypes. By multiplexing guide RNA genes, the vectors can modify up to four genes in a single round of editing. Whole-genome sequencing of base-edited isolates ofXanthomonas oryzaepv.oryzaerevealed guide RNA-independent off-target mutations. Further modifications of the CBE, using a CDA1 variant (CBE_RecAp-A) reduced off-target effects, providing an improved editing tool for a broad group of phytopathogenic bacteria.

 

Abstract Recently artificial intelligence (AI) and machine learning (ML) models have demonstrated remarkable progress with applications developed in various domains. It is also increasingly discussed that AI and ML models and applications should be transparent, explainable, and trustworthy. Accordingly, the field of Explainable AI (XAI) is expanding rapidly. XAI holds substantial promise for improving trust and transparency in AI-based systems by explaining how complex models such as the deep neural network (DNN) produces their outcomes. Moreover, many researchers and practitioners consider that using provenance to explain these complex models will help improve transparency in AI-based systems. In this paper, we conduct a systematic literature review of provenance, XAI, and trustworthy AI (TAI) to explain the fundamental concepts and illustrate the potential of using provenance as a medium to help accomplish explainability in AI-based systems. Moreover, we also discuss the patterns of recent developments in this area and offer a vision for research in the near future. We hope this literature review will serve as a starting point for scholars and practitioners interested in learning about essential components of provenance, XAI, and TAI. 

Abstract Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses. 

SWEETs play important roles in intercellular sugar transport. Induction of SWEET sugar transporters by Transcription Activator‐Like effectors (TALe) ofXanthomonasssp. is key for virulence in rice, cassava and cotton.

We identified OsSWEET11b with roles in male fertility and potential bacterial blight (BB) susceptibility in rice. While singleossweet11aor11bmutants were fertile, double mutants were sterile. As clade III SWEETs can transport gibberellin (GA), a key hormone for spikelet fertility, sterility and BB susceptibility might be explained by GA transport deficiencies. However, in contrast with the Arabidopsis homologues, OsSWEET11b did not mediate detectable GA transport. Fertility and susceptibility therefore are likely to depend on sucrose transport activity.

Ectopic induction ofOsSWEET11bby designer TALe enabled TALe‐freeXanthomonas oryzaepv.oryzae(Xoo) to cause disease, identifyingOsSWEET11bas a potential BB susceptibility gene and demonstrating that the induction of host sucrose uniporter activity is key to virulence ofXoo. Notably, only three of six clade III SWEETs are targeted by knownXoostrains from Asia and Africa.

The identification of OsSWEET11b is relevant for fertility and for protecting rice against emergingXoostrains that targetOsSWEET11b.