Table_1_Genome mining as a biotechnological tool for the discovery of novel biosynthetic genes in lichens.xlsx

Natural products (NPs) and their derivatives are a major contributor to modern medicine. Historically, microorganisms such as bacteria and fungi have been instrumental in generating drugs and lead compounds because of the ease of culturing and genetically manipulating them. However, the ever-increasing demand for novel drugs highlights the need to bioprospect previously unexplored taxa for their biosynthetic potential. Next-generation sequencing technologies have expanded the range of organisms that can be explored for their biosynthetic content, as these technologies can provide a glimpse of an organism’s entire biosynthetic landscape, without the need for cultivation. The entirety of biosynthetic genes can be compared to the genes of known function to identify the gene clusters potentially coding for novel products. In this study, we mine the genomes of nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and categorize the biosynthetic gene clusters (BGCs) as “associated product structurally known” or “associated product putatively novel”. Although lichen-forming fungi have been suggested to be a rich source of NPs, it is not known how their biosynthetic diversity compares to that of bacteria and non-lichenized fungi. We found that 25%–30% of biosynthetic genes are divergent as compared to the global database of BGCs, which comprises 1,200,000 characterized biosynthetic genes from plants, bacteria, and fungi. Out of 217 BGCs, 43 were highly divergant suggesting that they potentially encode structurally and functionally novel NPs. Clusters encoding the putatively novel metabolic diversity comprise polyketide synthases (30), non-ribosomal peptide synthetases (12), and terpenes (1). Our study emphasizes the utility of genomic data in bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial application of unexplored taxa. We highlight the untapped structural metabolic diversity encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first investigation identifying genes coding for NPs with potentially novel properties in lichenized fungi.</p

Table_2_Genome mining as a biotechnological tool for the discovery of novel biosynthetic genes in lichens.xlsx

Natural products (NPs) and their derivatives are a major contributor to modern medicine. Historically, microorganisms such as bacteria and fungi have been instrumental in generating drugs and lead compounds because of the ease of culturing and genetically manipulating them. However, the ever-increasing demand for novel drugs highlights the need to bioprospect previously unexplored taxa for their biosynthetic potential. Next-generation sequencing technologies have expanded the range of organisms that can be explored for their biosynthetic content, as these technologies can provide a glimpse of an organism’s entire biosynthetic landscape, without the need for cultivation. The entirety of biosynthetic genes can be compared to the genes of known function to identify the gene clusters potentially coding for novel products. In this study, we mine the genomes of nine lichen-forming fungal species of the genus Umbilicaria for biosynthetic genes, and categorize the biosynthetic gene clusters (BGCs) as “associated product structurally known” or “associated product putatively novel”. Although lichen-forming fungi have been suggested to be a rich source of NPs, it is not known how their biosynthetic diversity compares to that of bacteria and non-lichenized fungi. We found that 25%–30% of biosynthetic genes are divergent as compared to the global database of BGCs, which comprises 1,200,000 characterized biosynthetic genes from plants, bacteria, and fungi. Out of 217 BGCs, 43 were highly divergant suggesting that they potentially encode structurally and functionally novel NPs. Clusters encoding the putatively novel metabolic diversity comprise polyketide synthases (30), non-ribosomal peptide synthetases (12), and terpenes (1). Our study emphasizes the utility of genomic data in bioprospecting microorganisms for their biosynthetic potential and in advancing the industrial application of unexplored taxa. We highlight the untapped structural metabolic diversity encoded in the lichenized fungal genomes. To the best of our knowledge, this is the first investigation identifying genes coding for NPs with potentially novel properties in lichenized fungi.</p

The chromosomal distribution of piRNA clusters.

<p>Location of piRNA clusters on human chromosomes in A. Normal ovary, B. ENOCa and C. SOCa samples.</p

Expression profile of PIWIL genes and proteins in human normal ovarian and cancer tissues.

<p>A. The relative expression of thee PIWIL mRNAs analyzed by qRT-PCR analysis. The amount of PIWIL mRNAs was normalized to the endogenous control, β-actin mRNA. The fold-change was calculated based on the ratio of the normalized values of the ENOCa and SOCa to that of normal ovary. B. Western blot of three PIWIL proteins in normal ovary, ENOCa and SOCa.</p

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers

<div><p>PIWI-interacting (piRNAs), ~23–36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).</p></div

QC analysis of tissue samples of ENOCa, SOCa and normal ovary for small RNA sequencing and generation of reads.

<p>Agilent RNA Bioanalyzer profile of A. ENOCa; B. SOCa; C. normal ovary; D. RIN values revealing small RNA intactness optimal for sequencing; E. Number of trimmed reads of 16–40 nts generated from each sample type.</p

Characteristic properties of piRNAs identified in ENOCa, SOCa and normal ovary.

<p>A. Length and B. nucleotide bias observed among the piRNAs identified in each samples.</p

Canonical pathway(s) and network(s) enriched in SOCa.

<p>Canonical pathway(s) and network(s) enriched in SOCa.</p

piRNA-target duplexes in ENOCa and SOCa.

<p>A. The binding sites of piR-52207 with its targets NUDT4, MTR, EIF2S3 and MPHOSPH8 in ENOCa; B. The binding sites of piR-33733 and piR-52207 with its targets LIAS and ACTR10, PLEKHA5 respectively in SOCa.</p

The possible effects of piR-33733 and piR-52207 on target genes and subsequent pathophysiological consequences in SOCa.

<p>The possible effects of piR-33733 and piR-52207 on target genes and subsequent pathophysiological consequences in SOCa.</p