The Blast Fungus Decoded:Genomes in Flux

Plant disease outbreaks caused by fungi are a chronic threat to global food security. A prime case is blast disease, which is caused by the ascomycete fungus Magnaporthe oryzae (syn. Pyricularia oryzae), which is infamous as the most destructive disease of the staple crop rice. However, despite its Linnaean binomial name, M. oryzae is a multihost pathogen that infects more than 50 species of grasses. A timely study by P. Gladieux and colleagues (mBio 9:e01219-17, 2018, https://doi.org/10.1128/mBio.01219-17) reports the most extensive population genomic analysis of the blast fungus thus far. M. oryzae consists of an assemblage of differentiated lineages that tend to be associated with particular host genera. Nonetheless, there is clear evidence of gene flow between lineages consistent with maintaining M. oryzae as a single species. Here, we discuss these findings with an emphasis on the ecologic and genetic mechanisms underpinning gene flow. This work also bears practical implications for diagnostics, surveillance, and management of blast diseases

How to trick a plant pathogen?

Plants can get sick too. In fact, they get infected by all types of microbes and little critters. But plants have evolved an effective immune system to fight off pathogen invasion. Amazingly, nearly every single plant cell is able to protect itself and its neighbours against infections. The plant immune system gets switched on when one of its many immune receptors matches a ligand in the pathogen. As a consequence of a long evolutionary history of fighting off pathogens, immune receptors are now encoded by hundreds of genes that populate the majority of plant genomes. Understanding how the plant immune system functions and how it has evolved can give invaluable insights that would benefit modern agriculture and help breeding disease-resistant crops

The coming of age of EvoMPMI:evolutionary molecular plant-microbe interactions across multiple timescales

Plant-microbe interactions are great model systems to study co-evolutionary dynamics across multiple timescales. However, mechanistic research on plant-microbe interactions has often been conducted with little consideration of evolutionary concepts and methods. Conversely, evolutionary research has rarely integrated the range of mechanisms and models from the molecular plant-microbe interactions field. In recent years, the incipient field of evolutionary molecular plant-microbe interactions (EvoMPMI) has emerged to bridge this gap. Here, we report on some of the recent advances in EvoMPMI. In particular, we highlight new systems to study microbe interactions with early diverging land plants, and new findings from studies of adaptive evolution in pathogens and plants. By linking mechanistic and evolutionary research, EvoMPMI promises to expand our understanding of plant-microbe interactions

The role of screening questionnaires in the assessment of risk and severity of obstructive sleep apnea — polysomnography versus polygraphy

Obstructive sleep apnea (OSA) is a disease of significant importance, which may lead to numerous severe clinical consequences. The gold standard in the diagnosis of this sleep-related breathing disorder (SRBD) is polysomnography (PSG). However, due to the need for high expertise of staff who perform this procedure, its complexity, and relatively low availability, some simpler substitutes have been developed; among them is polygraphy (PG), which is most widely used.Also, there is a variety of questionnaires suitable to assess the pre-test probability and severity of OSA. The most frequently used ones are the STOP-BANG questionnaire (SBQ), NoSAS questionnaire, and Berlin questionnaire (BQ). However, they have different sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) when being used in various populations. The aim of this study is to provide a concise and clinically-oriented review of the most frequently used questionnaires, with special attention to its strengths and limitations. Moreover, we discuss whether PSG or PG would be more preferred for confirming OSA diagnosis with the highest likelihood

Regulation of human chorionic gonadotropin beta subunit expression in ovarian cancer

Expression of human chorionic gonadotropin beta subunit by cancers is extensively documented, yet regulation of the multiple genes that can code for this protein is poorly understood. The aim of the study was to examine the mechanisms regulating CGB gene expression in ovarian cancer. Expression of CGB genes and SP1, SP3, TFAP2A transcription factor genes was evaluated by RT-qPCR. The methylation status of CGB genes promoter regions was examined by methylation-specific PCR. mRNA arising from multiple CGB genes was detected in both ovarian control and malignant tissues. However, expression of CGB3-9 genes was shown to be significantly higher in malignant than healthy ovarian tissues. CGB1 and CGB2 transcripts were shown to be present in 20% of ovarian cancers, but were not detected in any of the control samples. Malignant tissues were characterized by DNA demethylation of CGB promoter regions. In ovarian cancer CGB expression positively correlated with TFAP2A transcripts level and expression of TFAP2A transcription factor was significantly higher in cancer than in control tissues. In contrast SP3 expression level was significantly lower in ovarian tumours than in control ovarian tissue. In ovarian cancers increased expression of human chorionic gonadotropin beta subunit is associated with demethylation of CGB promoter regions. CGB3-9 expression level strongly correlates with expression of the TFAP2A transcription factor. Presence of mRNA arising from CGB1 and CGB2 genes appears to be a unique feature of a subset of ovarian cancers

Mast cells influence neoangiogenesis in prostatic cancer independently of ERG status

A significant proportion of prostatic adenocarcinomas show recurrent translocation leading to ERG expression. Previously we found that ERG+ cases have higher microvessel density than negative ones. One factor influencing angiogenesis in cancer is mast cells. The aim of the present study was to evaluate the relationship between microvessels, mast cells and ERG status. Tissue microarrays prepared from 113 radical prostatectomy specimens were analyzed with immunohistochemistry for CD31, tryptase and chymase. Vascular profiles and tryptase-positive and chymase-positive cells were counted. The average number of tryptase-positive cells was 28.93/mm 2 and chymase-positive cells 9.91/mm 2 . The average number of CD31+ vascular profiles was 352.66/mm 2 . The average number of tryptase-positive cells was 26.35/mm 2 for ERG– cases and 32.12/mm 2 for ERG+ cases. The average number of chymase-positive cells was 8.14/mm 2 for ERG– cases and 12.06/mm 2 for ERG+ cases. The average number of CD31+ vascular profiles was 321.34/mm 2 for ERG– cases and 390.74/mm 2 for ERG+ cases. The number of CD31+ vascular profiles was positively correlated with the number of tryptase-positive and chymase-positive cells (R = 0.26 and R = 0.20). In summary, we demonstrated an interrelationship between mast cells, microvascular density and ERG status in prostatic carcinoma

Two NLR immune receptors acquired high-affinity binding to a fungal effector through convergent evolution of their integrated domain

A subset of plant NLR immune receptors carry unconventional integrated domains in addition to their canonical domain architecture. One example is rice Pik-1 that comprises an integrated heavy metal-associated (HMA) domain. Here, we reconstructed the evolutionary history of Pik-1 and its NLR partner, Pik-2, and tested hypotheses about adaptive evolution of the HMA domain. Phylogenetic analyses revealed that the HMA domain integrated into Pik-1 before Oryzinae speciation over 15 million years ago and has been under diversifying selection. Ancestral sequence reconstruction coupled with functional studies showed that two Pik-1 allelic variants independently evolved from a weakly binding ancestral state to high-affinity binding of the blast fungus effector AVR-PikD. We conclude that for most of its evolutionary history the Pik-1 HMA domain did not sense AVR-PikD, and that different Pik-1 receptors have recently evolved through distinct biochemical paths to produce similar phenotypic outcomes. These findings highlight the dynamic nature of the evolutionary mechanisms underpinning NLR adaptation to plant pathogens

Disentangling the complex gene interaction networks between rice and the blast fungus identifies a new pathogen effector

Studies focused solely on single organisms can fail to identify the networks underlying host–pathogen gene-for-gene interactions. Here, we integrate genetic analyses of rice (Oryza sativa, host) and rice blast fungus (Magnaporthe oryzae, pathogen) and uncover a new pathogen recognition specificity of the rice nucleotide-binding domain and leucine-rich repeat protein (NLR) immune receptor Pik, which mediates resistance to M. oryzae expressing the avirulence effector gene AVR-Pik. Rice Piks-1, encoded by an allele of Pik-1, recognizes a previously unidentified effector encoded by the M. oryzae avirulence gene AVR-Mgk1, which is found on a mini-chromosome. AVR-Mgk1 has no sequence similarity to known AVR-Pik effectors and is prone to deletion from the mini-chromosome mediated by repeated Inago2 retrotransposon sequences. AVR-Mgk1 is detected by Piks-1 and by other Pik-1 alleles known to recognize AVR-Pik effectors; recognition is mediated by AVR-Mgk1 binding to the integrated heavy metal-associated (HMA) domain of Piks-1 and other Pik-1 alleles. Our findings highlight how complex gene-for-gene interaction networks can be disentangled by applying forward genetics approaches simultaneously to the host and pathogen. We demonstrate dynamic coevolution between an NLR integrated domain and multiple families of effector proteins