Modeling knotted proteins with tangles

Although rare, an increasing number of proteins have been observed to contain entanglements in their native structures. To gain more insight into the significance of protein knotting, researchers have been investigating protein knot formation using both experimental and theoretical methods. Motivated by the hypothesized folding pathway of $\alpha$-haloacid dehalogenase (DehI) protein, Flapan, He, and Wong proposed a theory of how protein knots form, which includes existing folding pathways described by Taylor and B\"olinger et al. as special cases. In their topological descriptions, two loops in an unknotted open protein chain containing at most two twists each come close together, and one end of the protein eventually passes through the two loops. In this paper, we build on Flapan, He, and Wong's theory where we pay attention to the crossing signs of the threading process and assume that the unknotted protein chain may arrange itself into a more complicated configuration before threading occurs. We then apply tangle calculus, originally developed by Ernst and Sumners to analyze the action of specific proteins on DNA, to give all possible knots or knotoids that may be discovered in the future according to our model and give recipes for engineering specific knots in proteins from simpler pieces. We show why twists knots are the most likely knots to occur in proteins. We use chirality to show that the most likely knots to occur in proteins via Taylor's twisted hairpin model are the knots $+3_1$, $4_1$, and $-5_2$

Chromosome-level genome assembly and manually-curated proteome of model necrotroph Parastagonospora nodorum Sn15 reveals a genome-wide trove of candidate effector homologs, and redundancy of virulence-related functions within an accessory chromosome

Background: The fungus Parastagonospora nodorum causes septoria nodorum blotch (SNB) of wheat (Triticum aestivum) and is a model species for necrotrophic plant pathogens. The genome assembly of reference isolate Sn15 was first reported in 2007. P. nodorum infection is promoted by its production of proteinaceous necrotrophic effectors, three of which are characterised – ToxA, Tox1 and Tox3. Results: A chromosome-scale genome assembly of P. nodorum Australian reference isolate Sn15, which combined long read sequencing, optical mapping and manual curation, produced 23 chromosomes with 21 chromosomes possessing both telomeres. New transcriptome data were combined with fungal-specific gene prediction techniques and manual curation to produce a high-quality predicted gene annotation dataset, which comprises 13,869 high confidence genes, and an additional 2534 lower confidence genes retained to assist pathogenicity effector discovery. Comparison to a panel of 31 internationally-sourced isolates identified multiple hotspots within the Sn15 genome for mutation or presence-absence variation, which was used to enhance subsequent effector prediction. Effector prediction resulted in 257 candidates, of which 98 higher-ranked candidates were selected for in-depth analysis and revealed a wealth of functions related to pathogenicity. Additionally, 11 out of the 98 candidates also exhibited orthology conservation patterns that suggested lateral gene transfer with other cereal-pathogenic fungal species. Analysis of the pan-genome indicated the smallest chromosome of 0.4 Mbp length to be an accessory chromosome (AC23). AC23 was notably absent from an avirulent isolate and is predominated by mutation hotspots with an increase in non-synonymous mutations relative to other chromosomes. Surprisingly, AC23 was deficient in effector candidates, but contained several predicted genes with redundant pathogenicity-related functions. Conclusions: We present an updated series of genomic resources for P. nodorum Sn15 – an important reference isolate and model necrotroph – with a comprehensive survey of its predicted pathogenicity content

“CATAStrophy,” a Genome-Informed Trophic Classification of Filamentous Plant Pathogens – How Many Different Types of Filamentous Plant Pathogens Are There?

The traditional classification of fungal and oomycete phytopathogens into three classes – biotrophs, hemibiotrophs, or necrotrophs – is unsustainable. This study highlights multiple phytopathogen species for which these labels have been inappropriately applied. We propose a novel and reproducible classification based solely on genome-derived analysis of carbohydrate-active enzyme (CAZyme) gene content called CAZyme-Assisted Training And Sorting of -trophy (CATAStrophy). CATAStrophy defines four major divisions for species associated with living plants. These are monomertrophs (Mo) (corresponding to biotrophs), polymertrophs (P) (corresponding to necrotrophs), mesotrophs (Me) (corresponding to hemibiotrophs), and vasculartrophs (including species commonly described as wilts, rots, or anthracnoses). The Mo class encompasses symbiont, haustorial, and non-haustorial species. Me are divided into the subclasses intracellular and extracellular Me, and the P into broad and narrow host sub-classes. This gives a total of seven discrete plant-pathogenic classes. The classification provides insight into the properties of these species and offers a facile route to develop control measures for newly recognized diseases. Software for CATAStrophy is available online at https://github.com/ccdmb/catastrophy. We present the CATAStrophy method for the prediction of trophic phenotypes based on CAZyme gene content, as a complementary method to the traditional tripartite “biotroph–hemibiotroph–necrotroph” classifications that may encourage renewed investigation and revision within the fungal biology community.</p

Gender Identity, Disability, and Unmet Healthcare Needs among Disabled People Living in the Community in the United States

Disabled adults and transgender people in the United States face multiple compounding and marginalizing forces that result in unmet healthcare needs. Yet, gender identity among disabled people has not been explored, especially beyond binary categories of gender. Using cross-sectional survey data, we explored the rates of disability types and the odds of unmet healthcare needs among transgender people with disabilities compared to cisgender people with disabilities. The rates of disability type were similar between transgender and cisgender participants with two significant differences. Fewer transgender participants identified physical or mobility disability as their main disability compared to cisgender participants (12.31%/8 vs. 27.68/581, p < 0.01), and more transgender participants selected developmental disability as their main disability compared to cisgender participants (13.85%/9 vs. 3.67%/77, p < 0.001). After adjusting for sociodemographic characteristics, the odds of disabled transgender participants reporting an unmet need were higher for every unmet need except for preventative services

Hierarchical clustering of MS/MS spectra from the firefly metabolome identifies new lucibufagin compounds

Metabolite identification is the greatest challenge when analysing metabolomics data, as only a small proportion of metabolite reference standards exist. Clustering MS/MS spectra is a common method to identify similar compounds, however interrogation of underlying signature fragmentation patterns within clusters can be problematic. Previously published high-resolution LC-MS/MS data from the bioluminescent beetle (Photinus pyralis) provided an opportunity to mine new specialized metabolites in the lucibufagin class, compounds important for defense against predation. We aimed to 1) provide a workflow for hierarchically clustering MS/MS spectra for metabolomics data enabling users to cluster, visualise and easily interrogate the identification of underlying cluster ion profiles, and 2) use the workflow to identify key fragmentation patterns for lucibufagins in the hemolymph of P. pyralis. Features were aligned to their respective MS/MS spectra, then product ions were dynamically binned and resulting spectra were hierarchically clustered and grouped based on a cutoff distance threshold. Using the simplified visualization and the interrogation of cluster ion tables the number of lucibufagins was expanded from 17 to a total of 29

Saving energy, saving money : How South Carolina’s electric and natural gas utilities are using demand-side management to help customers reduce their energy bills, 2012

Demand-side management is a strategy that electric and natural gas utilities employ to decrease or defer demand for their energy services. The following report is intended to inform utility customers, consumer advocates, state and local policymakers, and energy market professionals about DSM activity undertaken by South Carolina’s electric and natural gas utilities in 2012, the last year for which Energy Information Agency data are available. Descriptions of DSM programs are based entirely on utility responses to the South Carolina Energy Office’s requests for information, as required by South Carolina Code of Laws Section 58-37-30

Crop-Zone Weed Mycobiomes of the South-Western Australian Grain Belt

In the absence of a primary crop host, secondary plant hosts may act as a reservoir for fungal plant pathogens of agricultural crops. Secondary hosts may potentially harbor heteroecious biotrophs (e.g., the stripe rust fungus Puccinia striiformis) or other pathogens with broad host ranges. Agricultural grain production tends toward monoculture or a limited number of crop hosts over large regions, and local weeds are a major source of potential secondary hosts. In this study, the fungal phyllospheres of 12 weed species common in the agricultural regions of Western Australia (WA) were compared through high-throughput DNA sequencing. Amplicons of D2 and ITS were sequenced on an Illumina MiSeq system using previously published primers and BLAST outputs analyzed using MEGAN. A heatmap of cumulative presence–absence for fungal taxa was generated, and variance patterns were investigated using principal components analysis (PCA) and canonical correspondence analysis (CCA). We observed the presence of several major international crop pathogens, including basidiomycete rusts of the Puccinia spp., and ascomycete phytopathogens of the Leptosphaeria and Pyrenophora genera. Unrelated to crop production, several endemic pathogen species including those infecting Eucalyptus trees were also observed, which was consistent with local native flora. We also observed that differences in latitude or climate zones appeared to influence the geographic distributions of plant pathogenic species more than the presence of compatible host species, with the exception of Brassicaceae host family. There was an increased proportion of necrotrophic Ascomycete species in warmer and drier regions of central WA, compared to an increased proportion of biotrophic Basidiomycete species in cooler and wetter regions in southern WA