Hotspot Regions Research Articles

Semirational Engineering of a Distal Loop Region to Enhance the Catalytic Activity and Stability of Leucine Dehydrogenase.

Enzymatic asymmetric synthesis of l-phenylglycine by amino acid dehydrogenases has potential for industrial applications; however, this is hindered by their low catalytic efficiency toward high-concentration substrates. We identified and characterized a novel leucine dehydrogenase (MsLeuDH) with a high catalytic efficiency for benzoylformic acid via directed metagenomic approaches. Further, we obtained a triple-point mutant MsLeuDH-EER (D332E/G333E/L334R) with improved stability and catalytic efficiency through the rational design of distal loop 13. A coexpression system of MsLeuDH-EER and formate dehydrogenase completely converted a 300 mM substrate within 4 h with >99.9% enantiomeric excess. Molecular dynamics simulations revealed that mutations on loop 13 enhanced the overall structural rigidity of the protein to improve its stability but also stabilized the "closed" conformation through rigidifying the hinge region loop by distant modulation. Our results show that distal loop 13 can serve as a new hotspot region for enhancing the catalytic performance of leucine dehydrogenases.

Plastid genome comparison and phylogenetic analyses of the Chinese group of medicinal species and related taxa within Asparagus genus

BackgroundAsparagus L. is a large genus widely distributed across the continents of the Old World. Among its members, approximately 14 species found in China are recognized as popular herbal medicines. However, accurate authentication of these medicinal species and their phylogenetic relationships with related taxa remains unresolved.MethodsTo identify simple sequence repeats (SSRs) and divergence hotspot regions appropriate for future authentication studies, as well as to infer the phylogenetic relationships among Asparagus species, we employed a plastid genome (plastome) dataset consisting of 25 Asparagus species (21 newly sequenced and four retrieved from GenBank), encompassing 12 Chinese medicinal species, for comparative and phylogenetic analyses.ResultsAll Asparagus plastomes displayed a typical quadripartite structure with sizes ranging from 155,948 bp to 157,128 bp and harbored 114 unique genes (80 protein-coding genes, 30 tRNA genes, and four rRNA genes). IRscope and Mauve analyses indicated minimal structural variation among Asparagus plastomes. We detected between 79 to 95 SSRs across the plastomes; most were located in the large single-copy (LSC) region and primarily consisted of mono-nucleotide repeat sequences (especially A and T repeats). The genus displayed mono-, di-, tri-, tetra-, penta-, and hexa-nucleotide repeats, but with variations in types and numbers among different species. Additionally, we identified 12 special SSR motifs and seven divergent hotspot regions that may serve as potential molecular markers for future identification efforts. Phylogenetic analyses yielded a robust phylogeny for Asparagus taxa, which were split into Clades I, II, and III. Notably, medicinal Asparagus species were mainly found in Clade III. Although the phylogenetic relationships of most Asparagus species aligned with previous study findings, the phylogenetic positions of A. munitus, A. subscandens, A. gobicus, and A. dauricus were newly determined.ConclusionsThe plastomes of Asparagus are largely conserved in terms of genome structure, size, gene content, and arrangement. Nevertheless, SSRs analyses revealed significant interspecific polymorphism within Asparagus. In addition, special SSR motifs and divergent hotspot regions identified from Asparagus plastomes provided reference for subsequent identification investigations. The plastome-based phylogeny provided preliminary insights into the relationships among the Chinese group of medicinal species and related taxa within Asparagus. Overall, this study offers a wealth of informative genetic resources pertinent to Asparagus, thereby enhancing our understanding of its evolution and laying a foundation for species identification, assessment of genetic population diversity, as well as the exploration and conservation of germplasm resources.

Comparative evaluation of antifungal susceptibility testing methods of invasive Candida species and detection of FKS genes mutations in caspofungin intermediate and resistant isolates

BackgroundFungal invasive infections caused by Candida species pose a substantial public health risk with limited therapeutic options. Antifungal susceptibility testing (AFST) is necessary to optimize the therapy. The study aimed to compare different AFST methods of Candida spp. and detect FKS gene mutations among caspofungin-intermediate and resistant isolates.MethodsA total of 60 non-replicative invasive Candida isolates recovered from various clinical samples were included. In-vitro AFST was carried out using the ATB FUNGUS 3, Vitek-2 AST-YS08, and E-test. Hotspot (HS) regions of FKS genes were sequenced for caspofungin-intermediate and resistant isolates.ResultsCandida albicans (58.3%) was the most predominant spp., followed by C. glabrata (28.3%). Based on the clinical breakpoints (CBPs), fluconazole resistance was found in C. albicans (45.7%), C. tropicalis (25%), and the C. parapsilosis isolate, while 35.3% of C. glabrata were susceptible dose-dependent (SDD). None of C. albicans, C. tropicalis, or C. parapsilosis isolates were resistant to voriconazole. Using the epidemiological cut-off values (ECVs) for amphotericin B, 6.7% of isolates were non-wild type (non-WT), including C. guilliermondii (50%), C. tropicalis (25%), and C. glabrata (11.8%), while all C. albicans, C. parapsilosis, and C. kefyr isolates were classified as wild-type (WT). ATB FUNGUS 3 and Vitek-2 had the highest categorical agreement (CA) (83.1%) for amphotericin B, while a lower concordance was detected with voriconazole (23.2%) and fluconazole (52.2%). For caspofungin, Vitek-2 and E-test had a CA of 89.8%. Eleven isolates (10 C. glabrata and one C. parapsilosis) exhibited resistance or intermediate susceptibility to caspofungin (MICs: 0.25‒>32 µg/ml). Molecular characterization of the FKS gene demonstrated that FKS1 mutations V47I, V52K, V56T, D57S, L62F, I71Y, I71Q in the HS1 region, and G7S, P11H mutations in the HS2 region were associated with increased caspofungin MIC values (16 µg/ml). Mutations at the HS1 of the FKS2 gene; K33V, W35K, and W35V; were associated with the highest caspofungin MICs of > 32 µg/ml.ConclusionsATB FUNGUS 3 demonstrated acceptable performance for AFST, however, azole activity against Candida spp. should be interpreted carefully. Novel mutations within HS regions of FKS genes elucidated different levels of caspofungin resistance in C. glabrata and C. parapsilosis isolates.

Super pan-genome reveals extensive genomic variations associated with phenotypic divergence in Actinidia

Kiwifruit is an economically and nutritionally important horticultural fruit crop worldwide. The genomic data of several kiwifruit species have been released, providing an unprecedented opportunity for pan-genome analysis to comprehensively investigate the inter- and intra-species genetic diversity and facilitate utilization for kiwifruit breeding. Here, we generated a kiwifruit super pan-genome using 15 high-quality assemblies of eight Actinidia species. For gene-based pan-genome, a total of 61,465 gene families were identified, and the softcore and dispensable genes were enriched in biological processes like response to endogenous stimulus, response to hormone and cell wall organization or biogenesis. Then, structural variations (SVs) against A. chinensis ‘Donghong’ were identified and then used to construct a graph-based genome. Further population-scale SVs based on resequencing data from 112 individuals of 20 species revealed extensive SVs which probably contributed to the phenotypic diversity among the Actinidia species. SV hotspot regions were found contributed to environmental adaptation. Furthermore, we systematically identified resistance gene analogs (RGAs) in the 15 assemblies and generated a pan-RGA dataset to reveal the diversity of genes potentially involved in disease resistance in Actinidia. The pan-genomic data obtained here is useful for evolutionary and functional genomic studies in Actinidia, and facilitates breeding design.

Characteristics of salt dust aerosols and their transport implications in the Aral Sea

Central Asia is an ecologically fragile arid zone and a typical mixed salt‒sand region. The socioeconomic and ecological problems attributed to the shrinking of the Aral Sea in Central Asia are notable concerns within the international community. In this study, the characteristics of salt dust aerosols from the Aral Sea were analysed to explore their interannual variation characteristics and analyse the spatial and temporal distributions of salt dust sources and transport and dispersion pathways. The results revealed that high concentrations of salt dust aerosols were concentrated around the Aral Sea and Lake Sarekamesh. The range and intensity of salt dust aerosols were less than those of dust aerosols. Salt dust events occurred frequently in spring and less frequently in autumn and winter. The occurrence frequency and impact range of salt dust aerosols from 2008 to 2012 were significantly lower than those during the previous period. From 2013 to 2018, the salt dust sources originated largely on the western side of the North Aral Sea. The spatial autocorrelation of salt dust aerosols was high and characterized by significant agglomeration, with significant changes in cold spot and hotspot regions. Salt dust in the Aral Sea region affects mainly the Kazakhstan region in spring, and it more notably affects Russia in winter. The results of this study increase the understanding of the spatial and temporal variability in salt dust aerosols within the arid zone of Central Asia and lay a foundation for the study of the impacts of salt dust aerosols on the climate system and ecological environment in arid zones.

P1203 Spatial mapping and geographic variation of inflammatory bowel disease in Canada: A population-based study using Statistics Canada data

Abstract Background Crohn’s Disease (CD) and Ulcerative Colitis (UC) pose significant challenges to patients and healthcare systems, with a rising incidence and prevalence globally1,2. To address the challenges of health resource allocation and understand the geographic distribution of these conditions in Canada, we conducted the spatial mapping of IBD across Canada using national population survey data available from Statistics Canada. Methods We utilized data from the 2009-2018 Canadian Community Health Survey (CCHS) to identify individuals with CD or UC. Prevalence rates, both crude and adjusted for age and sex, were calculated for each health region in Canada. Spatial dependencies between health regions were estimated using global Moran’s I and local indicators of spatial association (LISA) were used to identify clusters of health region (hot-spots) where the prevalence was significantly higher than in other areas. We further applied spatial simultaneous autoregressive lag models to explore the influence of region-level sociodemographic factors on identified spatial dependencies. Results A total of 492,560 individuals from 2010-2018 CCHS were included, representing 29,846,350 Canadians across 109 health regions. Survey data revealed that 0.38% of Canadians self-reported having CD and 0.47% reported having UC. The majority of respondents reported being urban-residing, middle-aged, and white. Across Canadian provinces, the age and sex-standardized prevalence of IBD ranged from 742 per 100,000 in Quebec to 1267 per 100,000 in Nova Scotia (Figure 1). Spatial analysis identified significant dependencies among health regions, but these spatial associations were explained by the differing distributions of sociodemographic characteristics in each health region (Table 1). Increased health region-level prevalence of CD and UC was associated with a larger proportion of individuals 30+ years, identifying as a female, immigrants, or as white (p<0.05 for each). Conclusion Data from this large, population-based Canadian national survey demonstrated significant geographic variation in the prevalence of CD and UC. However, after adjusting for patient demographic characteristics, the spatial dependency became non-significant. Key characteristics related to urbanization including the age distribution and proportion of immigrants in a health region were associated with increased prevalence rates. These results suggest that differences in CD and UC prevalence between geographic areas are primarily driven by individual demographics rather than differences in characteristics of local healthcare delivery systems and further support the notion that characteristics of urbanization increase the prevalence of IBD in an area1.

The accumulation of harmful genes within the ROH hotspot regions of the Tibetan sheep genome does not lead to genetic load

BackgroundProlonged natural selection and artificial breeding have contributed to increased uniformity within the Tibetan sheep population, resulting in a reduction in genetic diversity and the establishment of selective signatures in the genome. This process has led to a loss of heterozygosity in specific genomic regions and the formation of Runs of Homozygosity (ROH). Current research on ROH predominantly focuses on inbreeding and the signals of selection; however, there is a paucity of investigation into the genetic load and selective pressures associated with ROH, both within these regions and beyond. On one hand, genes located situated ROH hotspot regions exhibit a degree of conservation in their genomic segments; on the other hand, these regions may also serve as critical loci for identifying signals of selection.ResultsHigh-throughput re-sequencing technology was utilized to investigate the ROH hotspot regions across 11 Tibetan sheep populations, resulting in the identification of ten conserved genes (ARHGEF16, Tom1l2, PRDM16, PEMT, SREBF1, Rasd1, Nt5m, MED9, FLCN, RAI1) that are associated with lipid metabolism, lactation, and development. These genes exhibited highly conserved within the ROH hotspot regions across all Tibetan sheep populations. Employing the integrated haplotype score (iHS) method, we screened for selective sites within frequently observed ROH hotspot regions to elucidate genomic differences among Tibetan sheep populations. A comprehensive analysis was conducted, involving Rnhom, dN/dS ratios, missense/synonymous ratios, and loss-of-function (LOF)/synonymous ratios, to investigate the accumulation of deleterious genes and the associated genetic load both within and outside ROH hotspot regions. The results revealed a higher accumulation of deleterious genes and a reduced genetic load within the ROH regions.ConclusionsThis study provides a comprehensive and precise genomic analysis and interpretation of Tibetan sheep, offering theoretical basis for genetic breeding and evolution in Tibetan sheep.

Advancements and opportunities to improve bottom-up estimates of global wetland methane emissions

Abstract Wetlands are the single largest natural source of atmospheric methane (CH4), contributing approximately 30% of total surface CH4 emissions, and they have been identified as the largest source of uncertainty in the global CH4 budget based on the most recent Global Carbon Project (GCP) CH4 report. High uncertainties in the bottom-up estimates of wetland CH4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH4 emissions from space. In fact, there are large disagreements between bottom-up estimates versus top-down estimates inferred from inversion of atmospheric CH4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom-up estimates of global wetland CH4 emissions, as well as how they are used in top-down inversions. These bottom-up estimates, using (1) empirical biogeochemical modeling (e.g., WetCHARTs: 125 - 208 TgCH4 yr-1); (2) process-based biogeochemical modeling (e.g., WETCHIMP: 190 ± 39 TgCH4 yr-1); and (3) data-driven machine learning approach (e.g., UpCH4: 146 ± 43 TgCH4 yr-1), were all subject to large uncertainties (~80 TgCH4 yr-1). Major tropical and arctic wetland complexes are regional hotspots of CH4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top-down inversions to improve bottom-up estimates. Recent advances in surface measurements of CH4 fluxes (e.g., FLUXNET-CH4) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom-up estimates of wetland CH4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH4 observations directed at wetlands.

Dengue dynamics, predictions, and future increase under changing monsoon climate in India

The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities. Dengue mortality and meteorological conditions over a twelve-year period (2004–2015) are analyzed using statistical tools and machine learning methods. Our findings point to a significant influence of temperature, rainfall, and relative humidity on dengue mortality in Pune, at a time-lag of 2–5 months, providing sufficient lead time for an early warning targeted at curbing dengue outbreaks. We find that moderate rains spread over the summer monsoon season lead to an increase in dengue mortality, whereas heavy rains reduce it through the flushing effect, indicating the links between dengue and monsoon intraseasonal variability. Additionally, warm temperatures above 27°C and humidity levels between 60% and 78% elevate the risk of dengue. Based on these weather-dengue associations, we developed a machine-learning model utilizing the random forest regression algorithm. The dengue model yields a skillful forecast, achieving a statistically significant correlation coefficient of r = 0.77 and a relatively low Normalized Root Mean Squared Error score of 0.52 between actual and predicted dengue mortalities, at a lead time of two months. The model finds that the relative contributions of temperature, rainfall, and relative humidity to dengue mortality in Pune are 41%, 39%, and 20%, respectively. We use the dengue model in conjunction with the climate change simulations from the Coupled Model Intercomparison Project phase 6 for the future dengue mortality projections under a global warming scenario. In a changing climate, dengue-related mortality in Pune is projected to rise by 13% in the near future (2021–2040), 23–40% in the mid-century (2041–2060), and 30–112% in the late century (2081–2100) under low-to-high emission pathways in response to the associated increase in temperature and changes in monsoon rainfall patterns.

Assessing the predictive value of Ki-67 and progesterone receptor algorithms for recurrence and disease-free survival in meningiomas.

Sophisticated refinements in histopathology are evolving to improve meningioma outcome prediction. The aim of this study is to evaluate the stand-alone performance of Ki-67 and progesterone receptor (PR) algorithm scores in meningiomas and their power in predicting recurrence and disease-free survival of the patients. Whole slide images of Ki-67 and PR-stained slides from 404 meningioma cases were analyzed by a digital image viewer and analysis software Virapath-2.1, which analyzes the tumor cells by size, color, and shape. Ki-67 scores were calculated in the hotspot region that contains at least 1000 tumor cells, while PR was calculated on the whole slide. The results were compared with WHO grade, tumor recurrence and disease-free survival (DFS). Mean Ki-67 scores were 4.2±3.5, 12.1±10.6 and 22.±8.5 for grade 1, 2 and 3 tumors (p<0.05), while PR scores were 49±35, 43±34 and 16±30, respectively (p>0.05). Median survival of patients based on Ki-67 values ≤13.2% and>13.2% was 122 versus 60months (p=0.004). Prediction of recurrence based on Ki-67 score was found to have acceptable discrimination (AUC=0.74). PR expression was not found to correlate with DFS, but recurrent tumors had lower PR scores than non-recurrent tumors (31.3±33.8 vs. 49.0±33.0; p=0.03). Elevated Ki-67 levels identified by the algorithm may classify meningioma patients at high recurrence risk and inform clinical management. Although PR scores did not correlate with DFS, lower expression in recurrent tumors suggests a role in recurrence risk assessment. Larger prospective studies are needed for routine clinical practice.

A Special Insight on the Causal Agents and Mode of Occurrence of Japanese Encephalitis (JE) Infections in Rural Regions of Assam, India.

Japanese Encephalitis (JE) is a life-threatening disease, especially in the Indian subcontinent. Knowledge about the nature and ecology of the dispersal of JE virus (JEV) vectors needs to be increased. This study mechanistically explores the ecology of JEV vectors and the mode and frequency of occurrence of Acute Encephalitis Syndrome (AES) and JEV infections. We established a linear relationship between environmental variables and JEV infection by JEV vectors (mosquitoes)-Culex tritaeniorhynchus, Culex vishnui, and Culex pseudovishnui. The relative abundance of three mosquito species was evaluated, and the JE Sample Positivity Rate (SPR) and JE Case Fatality Rate (CFR) were computed. Culex vishnui had a high abundance in residential areas during the transition from hot-dry (77.34%) to hot-wet period (78.66%) at temperatures between 31°C and 34°C and relative humidity of 80%-85.3%; this period also coincided with occurrence of AES (39 cases in hot-dry and 88 cases in hot-wet period) and JE (8 instances in hot-dry and 31 cases in hot-wet period). JE infection dominated near rainfed rice fields (rainfall: R = 0.67 at p < 0.05; rainy days: R = 0.74, p < 0.01). SPR was up to 32.28%, and CFR was as high as 42.86%; JEV infection was concentrated in adult male humans near rice fields (15.66%). Climate modulation over the years can influence the distribution of Culex vishnui and, hence, AES and JE cases. JEV infections tend to rise in JE hotspot regions, especially near rice fields. Thus, comprehensive epidemiological investigations will help prevent a silent outbreak of JE.

Regional Hotspots of Change in Northern High Latitudes Informed by Observations From Space

Regional Hotspots of Change in Northern High Latitudes Informed by Observations From Space

Accelerating the diagnosis of Chinese cblC type MMA patients by multiplex PCR sequencing method.

CblC type methylmalonic aciduria (cblC disease) is the most common inborn error of vitamin B12 metabolism and due to mutations in the MMACHC gene. The earlier the diagnosis, the better the prognosis. Therefore, convenient and inexpensive detection method is needed. This study selected mutational hot-spot regions in the MMACHC gene which harbors more than 90% of mutant alleles responsible for cblC disease in China. Subsequently, a hot-spot regions multi-PCR Sanger sequencing method (HsRMSS) was designed. The accuracy and efficiency of HsRMSS was validated using samples from 20 cblC families with known MMACHC gene mutations and 50 healthy volunteers. In addition, patients' clinical phenotypes and molecular genetic features were analyzed. A total of 16 different mutations were identified in 20 cblC families. Among them, the most common mutations were c.609 G>A (26/80, 32.5%), c.567dupT (10/80, 12.5%), c.80A>G (8/80, 10.0%), c.658_660delAAG (8/80, 10.0%) and c.394C>T (6/80, 7.5%), which accounted for over 70% of disease alleles. The HsRMSS results were the same as the results using the whole exon sequencing, with a coincidence rate of 100%. The HsRMSS targeting the mutational hot-spots of MMACHC gene could be a promising tool to accurately and rapidly diagnose cblC disease in China. This study reported the development and validation of a hot-spot regions multi-PCR Sanger sequencing method for targeting hotspots which harbor most of the common MMACHC gene mutations reported in Chinese patients with cblC disease. The approach could have a potential clinical application as a rapid diagnosis and screening tool for suspected children with cblC type MMA and population carrier, owing to its high throughput, low cost, and high sensitivity and specificity.

Comparative Analysis of Complete Chloroplast Genomes and Phylogenetic Relationships of 21 Sect. Camellia (Camellia L.) Plants.

Background: Section Camellia is the most diverse group in the genus Camellia L., and this group of plants has a long history of cultivation in China as popular ornamental flowers and oil plants. Sect. Camellia plants present diverse morphological variations and complexity among species, resulting in uncertainty in the classification of species, which has resulted in a degree of inconvenience and confusion in the use of plant resources and research. Methods: Here, We sequenced and assembled the chloroplast genomes of 6 sect. Camellia and performed comparative chloroplast genome analysis and phylogenetic studies combined with 15 existing sect. Camellia plants. Results: The chloroplast genome of 21 species in sect. Camellia species were quadripartite with length of 156,587-157,068 bp base pairs (bp), and a highly conserved and moderately differentiated chloroplast genome arrangement. The 21 sect. Camellia chloroplast genomes were similar to those of angiosperms, with high consistency in gene number, gene content and gene structure. After the annotation process, we identified a total of 132 genes, specifically 87 sequences coding for proteins (CDS), 37 transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. The ycf1 gene in 21 species of the sect. Camellia was present only in the small single-copy/inverted repeat of a (SSC/IRa) region. Sequence variation was greater in the large single-copy (LSC) region than in the IR region, and the majority of the protein-coding genes presented high codon preferences. The chloroplast genomes of 21 plant species exhibit relatively conserved SC (single copy region)/IR (inverted repeat region) boundaries. We detected a total of 2975 single sequence repeats (SSRs) as well as 833 dispersed nuclear elements (INEs). Among these SSRs, A/T repeats and AT/AT repeats dominated, while among INEs, forward repeats and palindromic repeats predominated. Codon usage frequencies were largely similar, with 30 high-frequency codons detected. Comparative analysis revealed five hotspot regions (rps16, psaJ, rpl33, rps8, and rpl16) and two gene intervals (atpH-atpI and petD-rpoA) in the cp genome, which can be used as potential molecular markers. In addition, the phylogenetic tree constructed from the chloroplast genome revealed that these 21 species and Camellia oleifera aggregated into a single branch, which was further subdivided into two evolutionarily independent sub-branches. Conclusions: It was confirmed that sect. Camellia and C. oleifera Abel are closely related in Camellia genus. These findings will enhance our knowledge of the sect. Camellia of plants, deepen our understanding of their genetic characteristics and phylogenetic pathways, and provide strong support for the scientific development and rational utilization of the plant resources of the sect. Camellia.

Real-time cell barrier monitoring by spatial transepithelial electrical resistance measurement on a microelectrode array integrated Transwell.

Transepithelial electrical resistance (TEER) measurement is a label free, rapid and real-time technique, which is commonly used to evaluate the integrity of cell barriers. TEER characterization is important for applications, such as tissue (brain, intestines, lungs) barrier modeling, drug screening, and cell growth monitoring. Traditional TEER methods usually only show the average impedance of the whole cell layer, and lack accuracy and the characterization of internal spatial differences within cell layer regions. Here, we introduce a new spatial TEER strategy that utilizes microelectrode arrays (MEA) integrated in a Transwell to dynamically monitor TEER. A new electrical model which could reveal spatial impedance non-uniformity was proposed to extract accurate resistance from the measured data. Based on our method, the TEER signals from 16 different regions were successfully monitored in real time. The mapped impedance hotspots in different regions closely correlate with both fluorescence cell staining signals and calculated cell coverage, indicating the effectiveness of the developed spatial TEER system in monitoring local cell growth in vitro. The real-time spatial TEER responses to ethylene glycol-bis(β-aminoethylether)-N,N,N',N'-tetraacetic acid (EGTA) and cisplatin were studied, which could either reduce barrier integrity or inhibit cellular growth. The obtained results demonstrated the spatial TEER's applicability for cell barrier function and cell growth monitoring. Our approach provides accurate spatial electrical information of cell barriers and holds potential applications in drug development and screening.

Lower expression of BIN1's neuronal isoform in vulnerable excitatory neurons increases risk in Alzheimer's disease

Background: Neurons in Alzheimer's disease (AD) experience elevated DNA damage, with DNA repair sites enriched at enhancer regions of genes essential for neuronal survival. Excitatory neurons in the cortical superficial layers expressing CUX2 and RORB (Cux2+/Rorb+), are selectively vulnerable in AD, but their relationship to single nucleotide polymorphisms (SNPs) in AD genome-wide association studies (GWAS) is unclear. Objective: This study aimed to identify and characterize functional AD-GWAS SNPs using single-nucleus RNA sequencing data, focusing on selectively vulnerable neurons and DNA repair hotspots. Methods: Filters were applied to identify candidate SNPs based on overlap with repair hotspots, RNA expression, transcription factor binding, AD association, and epigenetic significance. In vitro assays and analyses of large datasets from bulk RNA-seq (n = 1894), proteomics (n = 400), and single-nucleus RNA-seq (n = 424, 1.6 M cells) were conducted. Results: BIN1 SNP, rs78710909, met multiple criteria - located in an AD-GWAS locus, repair hotspot, and promoter region. rs78710909C exhibits 1.52× higher AD risk and 5.4× differential transcription factor binding. In vitro, rs78710909C shows greater enhancer activity and weaker p53 but stronger E2F1 binding. BIN1's neuronal isoform is neuroprotective, but its AD expression is lower (p &lt; 0.01). Moreover, only in AD and Cux2+/Rorb + neurons, rs78710909C is associated with a lower average BIN1 neuronal isoform ratio (p &lt; 0.01). The genes upregulated in neurons with lower neuronal isoform ratio were associated with the hallmarks of AD pathology. Conclusions: In a disease-relevant mechanism, the BIN1 SNP rs78710909C is associated with a lower ratio of BIN1's neuronal isoform which increases the vulnerability of specific excitatory neurons in AD patients.

Long-Term Spatiotemporal Variation of Drought Patterns over Saudi Arabia

Understanding the historical patterns of drought changes is important to effectively manage and mitigate drought. This paper aims to provide a quantitative assessment of the spatiotemporal drought patterns in Saudi Arabia from 1985 to 2022. The study used the Standardized Precipitation Index (SPI) to examine drought patterns on both monthly and yearly timescales. The findings indicate a significant trend of increasing drought conditions in certain regions of the Kingdom from 1985 to 2022. The average rates of change for SPI-03, SPI-06, and SPI-12 were found to be −0.003 yr−1, −0.0034 yr−1, and −0.0099 yr−1, respectively. Droughts were more frequent and persistent in the northern regions of the country, while the western region experienced severe and intense droughts. There were fewer drought occurrences before 2000, but droughts became more frequent after 2000, with large-scale impacts occurring during 2007–2008 and 2013–2014. These findings have important implications for water management strategies and can help mitigate the effects of drought, as they identify hotspot regions across Saudi Arabia at different timescales. Overall, it is important to implement province-specific efforts to reduce environmental vulnerabilities to droughts.

Modeling Sediment Yield with Current and Projected Climatic Scenarios in Andit Tid Watershed, Central Highland of Ethiopia

Our ability to engage in long-term land management solutions that will benefit both land and water users is made possible by our understanding of how climate change affects sediment yield. This study aimed to determine the spatiotemporal distribution of sediment yield in the Andit Tid watershed as well as simulate sediment yield under existing and anticipated climate scenarios. SWAT and Arc GIS 10.5 software were used to estimate and map the spatial distribution of sediment yield. The annual average estimated sediment yield of the watershed was found to be 17.9 t ha-1 yr-1. The R2 was found to be 0.62 and 0.72 during calibration and validation of sediment yield. The projected average sediment yield up to 2098 under the wettest scenario is 13.7 t ha-1 in RCP 4.5 and 16.1 t ha-1 in RCP 8.5, respectively. It was discovered that, in comparison to the current average sediment, the near future (2022–2060) sediment was equal to it in RCP 4.5 and decreased by 41% in RCP 8.5, whereas the far future (2061–2098) sediment grew by 20.4% in RCP 8.5 and decreased by 35% in RCP 4.5. Out of the projected 76 years, 21 and 23 years showed positive deviations from the mean of the existing sediment yield under RCP 4.5 and 8.5, respectively. While in the driest scenario, the projected sediment yield was lower than the current rate, which was about 4 t ha-1 in both RCPs. In both current and future climate scenarios, the northeastern, eastern, and western regions were contributing to the higher sediment yield in the watershed. Most of these watershed hotspot regions were situated on farmed land with a slope of more than twenty percent and active gullies. When developing and executing management solutions in the areas that are severely impacted, the watershed community and decision-makers are recommended to make use of the spatial distribution map. It is also necessary to take steps to lessen the likelihood that the emission scenarios that result in RCP 8.5 will occur.

Exploring the phylogenetic framework and trait evolution of Impatiens through chloroplast genome analysis

BackgroundThe genus Impatiens, which includes both annual and perennial herbs, holds considerable ornamental, economic, and medicinal value. However, it posed significant challenges for taxonomic and systematic reconstruction. This was largely attributed to its high intraspecific diversity and low interspecific variation in morphological characteristics. In this study, we sequenced samples from 12 Impatiens species native to China and assessed their phylogenetic resolution using the complete chloroplast genome, in conjunction with published samples of Impatiens. In addition, a comparative analysis of chloroplast genomes were conducted to explore the evolution of the chloroplast genome in Impatiens.ResultsThe chloroplast genomes of 12 Impatiens species exhibited high similarity to previously published samples in terms of genome size, gene content, and sequence. The chloroplast genome of Impatiens exhibited a typical four-part structure, with lengths ranging from 146,987 bp(I. morsei)- 152,872 bp(I. jinpingensis). Our results identified 10 mutant hotspot regions (rps16, rps16-trnG, trnS-trnR, and rpoB-trnC) that could serve as effective molecular markers for phylogenetic analyses and species identification within the Impatiens. Phylogenetic analyses supported the classification of Impatiens as a monophyletic taxon. The identified affinities supported the taxonomic classification of the subgenus Clavicarpa within the Impatiens, with subgenus Clavicarpa being the first taxon to diverge. In phylogenetic tree,the Impatiens was divided into eight distinct clades. The results of ancestral trait reconstruction suggested that the ancestral traits of Impatiens included a perennial life cycle, four sepals and three pollen grooves. However, the ancestral morphology regarding fruit shape, flower colour, and spacing length remained ambiguous.ConcludeOur study largely supported the family-level taxonomic treatment of Impatiens species in China and demonstrated the utility of whole chloroplast genome sequences for phylogenetic resolution. Comparative analysis of the chloroplast genomes of Impatiens facilitated the development of molecular markers.The results of ancestral trait reconstruction showed that the ancestor type of habit was perennial, the number of sepals was 4, and morphology and number of aperture was 3 colpus. The traits of capsule shape, flower colour, and spur length underwent a complex evolutionary process. Our results provided data support for further studies and some important new insights into the evolution of the Impatiens.

Genome-wide mapping of spontaneous DNA replication error-hotspots using mismatch repair proteins in rapidly proliferating Escherichia coli.

Fidelity of DNA replication is crucial for the accurate transmission of genetic information across generations, yet errors still occur despite multiple control mechanisms. This study investigated the factors influencing spontaneous replication errors across the Escherichia coli genome. We detected errors using the MutS and MutL mismatch repair proteins in rapidly proliferating mutH-deficient cells, where errors can be detected but not corrected. Our findings reveal that replication error hotspots are non-randomly distributed along the chromosome and are enriched in sequences with distinct features: lower thermal stability facilitating DNA strand separation, mononucleotide repeats prone to DNA polymerase slippage and sequences prone to forming secondary structures like cruciforms and G4 structures, which increase likelihood of DNA polymerase stalling. These hotspots showed enrichment for binding sites of nucleoid-associated proteins, RpoB and GyrA, as well as highly expressed genes, and depletion of GATC sequence. Finally, the enrichment of single-stranded DNA stretches in the hotspot regions establishes a nexus between the formation of secondary structures, transcriptional activity and replication stress. In conclusion, this study provides a comprehensive genome-wide map of replication error hotspots, offering a holistic perspective on the intricate interplay between various mechanisms that can compromise the faithful transmission of genetic information.