Bat-associated microbes: Opportunities and perils, an overview.

The potential biotechnological uses of bat-associated bacteria are discussed briefly, indicating avenues for biotechnological applications of bat-associated microbes. The uniqueness of bats in terms of their lifestyle, genomes and molecular immunology may predispose bats to act as disease reservoirs. Molecular phylogenetic analysis has shown several instances of bats harbouring the ancestral lineages of bacterial (Bartonella), protozoal (Plasmodium, Trypanosoma cruzi) and viral (SARS-CoV2) pathogens infecting humans. Along with the transmission of viruses from bats, we also discuss the potential roles of bat-associated bacteria, fungi, and protozoan parasites in emerging diseases. Current evidence suggests that environmental changes and interactions between wildlife, livestock, and humans contribute to the spill-over of infectious agents from bats to other hosts. Domestic animals including livestock may act as intermediate amplifying hosts for bat-origin pathogens to transmit to humans. An increasing number of studies investigating bat pathogen diversity and infection dynamics have been published. However, whether or how these infectious agents are transmitted both within bat populations and to other hosts, including humans, often remains unknown. Metagenomic approaches are uncovering the dynamics and distribution of potential pathogens in bat microbiomes, which might improve the understanding of disease emergence and transmission. Here, we summarize the current knowledge on bat zoonoses of public health concern and flag the gaps in the knowledge to enable further research and allocation of resources for tackling future outbreaks.

Isolation of Pikps, an allele of Pik, from the aus rice cultivar Shoni.

Blast disease caused by the filamentous fungus Pyricularia oryzae (syn. Magnaporthe oryzae) is one of the most destructive diseases of rice (Oryza sativa L.) around the globe. An aus cultivar, Shoni, showed resistance against at least four Japanese P. oryzae isolates. To understand Shoni's resistance against the P. oryzae isolate Naga69-150, genetic analysis was carried out using recombinant inbred lines developed by a cross between Shoni and the japonica cultivar Hitomebore, which is susceptible to Naga69-150. The result indicated that the resistance was controlled by a single locus, which was named Pi-Shoni. A QTL analysis identified Pi-Shoni as being located in the telomeric region of chromosome 11. A candidate gene approach in the region indicated that Pi-Shoni corresponds to the previously cloned Pik locus, and we named this allele Pikps. Loss of gene function mediated by RNA interference demonstrated that a head-to-head-orientated pair of NBS-LRR receptor genes (Pikps-1 and Pikps-2) are required for the Pikps-mediated resistance. Amino acid sequence comparison showed that Pikps-1 is 99% identical to Pikp-1, while Pikps-2 is identical to Pikp-2. Pikps-1 had one amino acid substitution (Pro351Ser) in the NBS domain as compared to Pikp-1. The recognition specificity of Pikps against known AVR-Pik alleles is identical to that of Pikp.

An informatics approach to distinguish RNA modifications in nanopore direct RNA sequencing.

Modifications in RNA can influence their structure, function, and stability and play essential roles in gene expression and regulation. Methods to detect RNA modifications rely on biophysical techniques such as chromatography or mass spectrometry, which are low throughput, or on high throughput short-read sequencing techniques based on selectively reactive chemical probes. Recent studies have utilized nanopore-based fourth-generation sequencing methods to detect modifications by directly sequencing RNA in its native state. However, these approaches are based on modification-associated mismatch errors that are liable to be confounded by SNPs. Also, there is a need to generate matched knockout controls for reference, which is laborious. In this work, we introduce an internal comparison strategy termed "IndoC," where features such as 'trace' and 'current signal intensity' of potentially modified sites are compared to similar sequence contexts on the same RNA molecule within the sample, alleviating the need for matched knockout controls. We first show that in an IVT model, 'trace' is able to distinguish between artificially generated SNPs and true pseudouridine (Ψ) modifications, both of which display highly similar mismatch profiles. We then apply IndoC on yeast and human ribosomal RNA to demonstrate that previously reported Ψ sites show marked changes in their trace and signal intensity profiles compared with their unmodified counterparts in the same dataset. Finally, we perform direct RNA sequencing of RNA containing Ψ intact with a chemical probe adduct (N-cyclohexyl-N'-ß-(4-methylmorpholinium) ethylcarbodiimide [CMC]) and show that CMC reactivity also induces changes in trace and signal intensity distributions in a Ψ specific manner, allowing their separation from high mismatch sites that display SNP-like behavior.