Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems
The resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and exact integer linear programing (EILP) solvers. Using a case study in BC, Canada, we compare the cost-effectiveness and processing times of SA used in Marxan versus EILP using both commercial and open-source algorithms. Plans for expanding protected area systems based on EILP algorithms were 12–30% cheaper than plans using SA, due to EILP’s ability to find optimal solutions as opposed to approximations. The best EILP solver we examined was on average 1,071 times faster than the SA algorithm tested. The performance advantages of EILP solvers were also observed when we aimed for spatially compact solutions by including a boundary penalty. One practical advantage of using EILP over SA is that the analysis does not require calibration, saving even more time. Given the performance of EILP solvers, they can be used to generate conservation plans in real-time during stakeholder meetings and can facilitate rapid sensitivity analysis, and contribute to a more transparent, inclusive, and defensible decision-making process.
Spatial and Geographic Information Science
Schuster et al. (2020) Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems. PeerJ 8:e9258 https://doi.org/10.7717/peerj.9258
Bioinformatics profiling identifies seven immune-related risk signatures for hepatocellular carcinoma
Background Density of tumor infiltrating lymphocytes (TIL) and expressions of certain immune-related genes have prognostic and predictive values in hepatocellular carcinoma (HCC); however, factors determining the immunophenotype of HCC patients are still unclear. In the current study, the transcript sequencing data of liver cancer were systematically analyzed to determine an immune gene marker for the prediction of clinical outcome of HCC. Methods RNASeq data and clinical follow-up information were downloaded from The Cancer Genome Atlas (TCGA), and the samples were assigned into high-stage and low-stage groups. Immune pathway-related genes were screened from the Molecular Signatures Database v4.0 (MsigDB) database. LASSO regression analysis was performed to identify robust immune-related biomarkers in predicting HCC clinical outcomes. Moreover, an immune gene-related prognostic model was established and validated by test sets and Gene Expression Omnibus (GEO) external validation sets. Results We obtained 319 immune genes from MsigDB, and the genes have different expression profiles in high-stage and low-stage of HCC. Univariate survival analysis found that 17 genes had a significant effect on HCC prognosis, among them, 13 (76.5%) genes were prognostically protective factors. Further lasso regression analysis identified seven potential prognostic markers (IL27, CD1D, NCOA6, CTSE, FCGRT, CFHR1, and APOA2) of robustness, most of which are related to tumor development. Cox regression analysis was further performed to establish a seven immune gene signature, which could stratify the risk of samples in training set, test set and external verification set (p < 0.01), and the AUC in both training set and test set was greater than 0.85, which also greater compared with previous studies. Conclusion This study constructed a 7-immunogenic marker as novel prognostic markers for predicting survival of HCC patients.
Xue et al. (2020) Bioinformatics profiling identifies seven immune-related risk signatures for hepatocellular carcinoma. PeerJ 8:e8301 https://doi.org/10.7717/peerj.8301
Descriptions of five new species of the salamander genus Chiropterotriton (Caudata: Plethodontidae) from eastern Mexico and the status of three currently recognized taxa
The genus Chiropterotriton is endemic to Mexico with a geographical distribution along the Sierra Madre Oriental, the Trans Mexican Volcanic Belt and the Sierra de Juárez. The recent use of molecular tools has shown that Mexico’s amphibian diversity is highly underestimated, including a large number of cryptic, unnamed species. Chiropterotriton has 18 described species including terrestrial, arboreal and cave-dwelling species. In previous molecular studies, the presence of multiple undescribed species was evident. We present a phylogenetic hypothesis based on mitochondrial data, which includes all described species and six undescribed taxa. Based on the morphological analyses and, when available, combined with molecular data, we describe five new species of the genus; Chiropterotriton casasi sp. nov., C. ceronorum sp. nov., C. melipona sp. nov., C. perotensis sp. nov. and C. totonacus sp. nov. In addition, we redescribe two others: Chiropterotriton chiropterus and C. orculus, and provide a comparable account of one additional sympatric congener. This increases the number of species in the genus to 23, which represent a considerable component of Mexican plethodontid richness.
Parra Olea et al. (2020) Descriptions of five new species of the salamander genus Chiropterotriton (Caudata: Plethodontidae) from eastern Mexico and the status of three currently recognized taxa. PeerJ 8:e8800 https://doi.org/10.7717/peerj.8800
Effective connectivity differences in motor network during passive movement of paretic and non-paretic ankles in subacute stroke patients
Background A better understanding of the neural changes associated with paresis in stroke patients could have important implications for therapeutic approaches. Dynamic Causal Modeling (DCM) for functional magnetic resonance imaging (fMRI) is commonly used for analyzing effective connectivity patterns of brain networks due to its significant property of modeling neural states behind fMRI signals. We applied this technique to analyze the differences between motor networks (MNW) activated by continuous passive movement (CPM) of paretic and non-paretic ankles in subacute stroke patients. This study aimed to identify CPM induced connectivity characteristics of the primary sensory area (S1) and the differences in extrinsic directed connections of the MNW and to explain the hemodynamic differences of brain regions of MNW. Methods For the network analysis, we used ten stroke patients’ task fMRI data collected under CPMs of both ankles. Regions for the MNW, the primary motor cortex (M1), the premotor cortex (PM), the supplementary motor area (SMA) and the S1 were defined in a data-driven way, by independent component analysis. For the network analysis of both CPMs, we compared twelve models organized into two model-families, depending on the S1 connections and input stimulus modeling. Using DCM, we evaluated the extrinsic connectivity strengths and hemodynamic parameters of both stimulations of all patients. Results After a statistical comparison of the extrinsic connections and their modulations of the “best model”, we concluded that three contralateral self-inhibitions (cM1, cS1 and cSMA), one contralateral inter-regional connection (cSMA→cM1), and one interhemispheric connection (cM1→iM1) were significantly different. Our research shows that hemodynamic parameters can be estimated with the Balloon model using DCM but the parameters do not change with stroke. Conclusions Our results confirm that the DCM-based connectivity analyses combined with Bayesian model selection may be a useful technique for quantifying the alteration or differences in the characteristics of the motor network in subacute stage stroke patients and in determining the degree of MNW changes.
Nagy et al. (2020) Effective connectivity differences in motor network during passive movement of paretic and non-paretic ankles in subacute stroke patients. PeerJ 8:e8942 https://doi.org/10.7717/peerj.8942
Microbiome analysis of healthy and diseased sponges Lubomirskia baicalensis by using cell cultures of primmorphs
Endemic sponges (Demosponges, Lubomirskiidae) dominate the fauna of the littoral zone of Lake Baikal. These freshwater sponges live in symbiosis with diverse eukaryotes and prokaryotes, including chlorophyll-containing microalgae. Within the last 5 years, the incidence of sponge disease and mortality events in Lake Baikal has increased. The etiology and ecology of these events remain unknown, in part because of the lack of models to study sponge-microbe interactions. In this work, we tested the use of primmorph cell cultures of Lubomirskia baicalensis as a tool for investigating the microbiomes of sponges. We infected primmorphs, cultured in vitro, with samples from diseased sponges and observed, by microscopy, disease symptoms, including loss of green symbionts, associated with mass die-off events. Subsequent sequencing of 16S rRNA gene fragments revealed that the microbiome community of healthy sponge and primmorphs formed a group separate from the community of diseased sponges and infected primmorphs. This confirms the suitability of the primmorph cell culture as a model sponge system. We also discovered mass mortality of green symbionts (Chlorophyta) was associated with a shift in the microbial communities of sponges/primmorphs. Microbes in diseased sponges, and infected primmorphs, belonged mainly to the phyla Bacteroidetes and Proteobacteria and these families Flavobacteriaceae, Burkholderiaceae, and Moraxellaceae. Primmorphs cell culture may provide a model to study interactions between these bacteria and their host and elucidate the cause of mass mortality events.
Chernogor et al. (2020) Microbiome analysis of healthy and diseased sponges Lubomirskia baicalensis by using cell cultures of primmorphs. PeerJ 8:e9080 https://doi.org/10.7717/peerj.9080
Cca-miR398 increases copper sulfate stress sensitivity via the regulation of CSD mRNA transcription levels in transgenic Arabidopsis thaliana
MicroRNAs play crucial roles during the process of plant development under stress conditions. Copper is an essential micronutrient for most organisms and serves as an important redox-active cofactor for various functional proteins. In the present study, we investigated the effects of copper sulfate stress on hickory (Carya cathayensis) root development. We identified that hickory cca-miR398 was related to copper sulfate stress response, targeting Copper/Zinc superoxide dismutases (cytosolic (CSD1) and chloroplastic (CSD2)) and a 5b subunit of mitochondrial cytochrome C oxidase (COX5b.1) that are linked directly to stress regulatory networks. The sequence of hickory cca-miR398 is highly similar to that of Arabidopsis miR398b and miR398c, regardless of one nucleotide variation. Therefore, target genes of cca-miR398 were investigated by using 5′-Rapid-amplification of cDNA ends. An overexpression of cca-miR398 in Arabidopsis caused a reduction not only in root length and cotyledon greening, but also in the CSD1, CSD2, and CSD3 transcription levels. These reductions had greater significance in transgenic Arabidopsis than in wild-type Arabidopsis under copper sulfate stress. The level of physiological indicators also changed in transgenic Arabidopsis. In addition, the expressions of copper-responsive microRNAs, such as miR397 and miR408, were affected by the copper sulfate stress. These results showed that CSD possesses the ability to enhance copper sulfate stress response in both transgenic Arabidopsis and hickory roots by increasing the production of superoxide dismutase. Our results also demonstrated that cca-miR398 weakens hickory tolerance to copper sulfate by regulating CSD targets.
Sun et al. (2020) Cca-miR398 increases copper sulfate stress sensitivity via the regulation of CSD mRNA transcription levels in transgenic Arabidopsis thaliana. PeerJ 8:e9105 https://doi.org/10.7717/peerj.9105
The combined effects of light intensity, temperature, and water potential on wall deposition in regulating hypocotyl elongation of Brassica rapa
Hypocotyl elongation is a critical sign of seed germination and seedling growth, and it is regulated by multi-environmental factors. Light, temperature, and water potential are the major environmental stimuli, and their regulatory mechanism on hypocotyl growth has been extensively studied at molecular level. However, the converged point in signaling process of light, temperature, and water potential on modulating hypocotyl elongation is still unclear. In the present study, we found cell wall was the co-target of the three environmental factors in regulating hypocotyl elongation by analyzing the extension kinetics of hypocotyl and the changes in hypocotyl cell wall of Brassica rapa under the combined effects of light intensity, temperature, and water potential. The three environmental factors regulated hypocotyl cell elongation both in isolation and in combination. Cell walls thickened, maintained, or thinned depending on growth conditions and developmental stages during hypocotyl elongation. Further analysis revealed that the imbalance in wall deposition and hypocotyl elongation led to dynamic changes in wall thickness. Low light repressed wall deposition by influencing the accumulation of cellulose, hemicellulose, and pectin; high temperature and high water potential had significant effects on pectin accumulation overall. It was concluded that wall deposition was tightly controlled during hypocotyl elongation, and low light, high temperature, and high water potential promoted hypocotyl elongation by repressing wall deposition, especially the deposition of pectin.
Wang et al. (2020) The combined effects of light intensity, temperature, and water potential on wall deposition in regulating hypocotyl elongation of Brassica rapa. PeerJ 8:e9106 https://doi.org/10.7717/peerj.9106
At the crossroads of botanical collections and molecular genetics laboratory: a preliminary study of obtaining amplifiable DNA from moss herbarium material
Background Research focused on extreme environments is often associated with difficulties in obtaining fresh plant material. Herbaria may provide great support as they house large collections of specimens from different parts of the world. Accordingly, there is also a growing interest in methods using herbarium specimens in molecular studies. Much of the literature on herbarium DNA is aimed to improve extraction and PCR amplification and is focused mostly on vascular plants. Here, I provide a brief study of DNA extraction efficiency from moss herbarium specimens, emphasizing the importance of herbaria as an invaluable source of material from hard-to-access geographical areas, such as the Antarctic region. Methods The presented study is based on herbarium collections of 25 moss species collected in the austral polar regions between 1979 and 2013. The majority of samples were obtained using the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany). The remaining, smaller part was extracted using an adapted CTAB-based approach. The performance of DNA extraction methods in terms of PCR amplification success was measured by testing several DNA fragments of various size. Furthermore, in order to estimate of DNA fragmentation level, an automated on-chip electrophoresis system was used. Results Results reveal that DNA purity and the length of the target genetic region are the fundamental agents which drive the successful PCR reaction. Conversely, the DNA yield and specimen age seem to be less relevant. With this study, I present also an optimized CTAB-based approach which may effectively suppress inhibitors in the herbarium DNA. This method can be considered a cheaper alternative to column-based technology, particularly useful for dealing with a large number of samples. Results of this study confirmed previous reports and contribute to filling the existing gap in molecular analyses which involve the use of herbarium collections of mosses.
Saługa (2020) At the crossroads of botanical collections and molecular genetics laboratory: a preliminary study of obtaining amplifiable DNA from moss herbarium material. PeerJ 8:e9109 https://doi.org/10.7717/peerj.9109
Characterization of the bacterial microbiota composition and evolution at different intestinal tract in wild pigs (Sus scrofa ussuricus)
Commensal microorganisms are essential to the normal development and function of many aspects of animal biology, including digestion, nutrient absorption, immunological development, behaviors, and evolution. The specific microbial composition and evolution of the intestinal tracts of wild pigs remain poorly characterized. This study therefore sought to assess the composition, distribution, and evolution of the intestinal microbiome of wild pigs. For these analyses, 16S rRNA V3-V4 regions from five gut sections prepared from each of three wild sows were sequenced to detect the microbiome composition. These analyses revealed the presence of 6,513 operational taxonomic units (OTUs) mostly distributed across 17 phyla and 163 genera in these samples, with Firmicutes and Actinobacteria being the most prevalent phyla of microbes present in cecum and jejunum samples, respectively. Moreover, the abundance of Actinobacteria in wild pigs was higher than that in domestic pigs. At the genus level the Bifidobacterium and Allobaculum species of microbes were most abundant in all tested gut sections, with higher relative abundance in wild pigs relative to domestic pigs, indicating that in the process of pig evolution, the intestinal microbes also evolved, and changes in the intestinal microbial diversity could have been one of the evolutionary forces of pigs. Intestinal microbial functional analyses also revealed the microbes present in the small intestine (duodenum, jejunum, and ileum) and large intestine (cecum and colon) of wild pigs to engage distinct metabolic spatial structures and pathways relative to one another. Overall, these results offer unique insights that would help to advance the current understanding of how the intestinal microbes interact with the host and affect the evolution of pigs.
Yang et al. (2020) Characterization of the bacterial microbiota composition and evolution at different intestinal tract in wild pigs (Sus scrofa ussuricus). PeerJ 8:e9124 https://doi.org/10.7717/peerj.9124
An improved similarity-based approach to predicting and mapping soil organic carbon and soil total nitrogen in a coastal region of northeastern China
Soil organic carbon (SOC) and soil total nitrogen (STN) are major soil indicators for soil quality and fertility. Accurate mapping SOC and STN in soils would help both managed and natural soils and ecosystem management. This study developed an improved similarity-based approach (ISA) to predicting and mapping topsoil (0–20 cm soil depth) SOC and STN in a coastal region of northeastern China. Six environmental variables including elevation, slope gradient, topographic wetness index, the mean annual temperature, the mean annual temperature, and normalized difference vegetation index were used as predictors. Soil survey data in 2012 was designed based on the clustering of the study area into six climatic vegetation landscape units. In each landscape unit, 20–25 sampling points were determined at different landform positions considering local climate, soil type, elevation and other environmental factors, and finally 126 sampling points were obtained. Soil sampling from the depth of 0–20 cm were used for model prediction and validation. The ISA model performance was compared with the geographically weighted regression (GWR), regression kriging (RK), boosted regression trees (BRT) considering mean absolute prediction error (MAE), root mean square error (RMSE), coefficient of determination (R2), and maximum relative difference (RD) indices. We found that the ISA method performed best with the highest R2 and lowest MAE, RMSE compared to GWR, RK, and BRT methods. The ISA method could explain 76% and 83% of the total SOC and STN variability, respectively, 12–40% higher than other models in the study area. Elevation had the largest influence on SOC and STN distribution. We conclude that the developed ISA model is robust and effective in mapping SOC and STN, particularly in the areas with complex vegetation-landscape when limited samples are available. The method needs to be tested for other regions in our future research.
Wang et al. (2020) An improved similarity-based approach to predicting and mapping soil organic carbon and soil total nitrogen in a coastal region of northeastern China. PeerJ 8:e9126 https://doi.org/10.7717/peerj.9126