Identification Of Species Research Articles

Expansion of the multi-locus gene alignment approach to improve identification of the fungal species Alternaria alternata

Alternaria alternata is part of a genus comprised of over 600 different species that occur all over the world and cause damage to humans, plants and thereby to the economy. Yet, even though some species are causing tremendous issues, the past years have shown that assigning newly found isolates to known species was rather inconsistent. Most identifications are usually done on the basis of spore morphology, chemotype and molecular markers. In this work we used strains isolated from the wild as well as commercial strains of the DSMZ (German collection of microorganisms and cell cultures) as a reference, to show, that the variation within the Alternaria alternata species is comparable to the variation between different species of the genus Alternaria in regards to spore morphology and chemotype. We compared the different methods of identification and discerned the concatenation of multiple molecular markers as the deciding factor for better identification. Up until this point, usually a concatenation of two or three traditional molecular markers was used. Some of those markers being stronger some weaker. We show that the concatenation of five molecular markers improves the likeliness of a correct assignment, thus a better distinction between the different Alternaria species.

Multiparameter optimization of non-thermal plasma-driven synthesis of carbohydrate-stabilized rhenium nanoparticles towards enhancement of their catalytical activity for reduction of nitroaromatic compounds

This study aims to optimize the synthesis of carbohydrate-stabilized rhenium nanoparticles (ReNPs) utilizing cold atmospheric pressure plasma (CAPP), specifically direct current atmospheric pressure glow discharge (dc-APGD), hypothesizing that controlling synthesis parameters will enhance catalytic efficiency in the reduction of nitroaromatic compounds (NACs). The dc-APGD system operated in flowing liquid cathode (FLC-dc-APGD) and flowing liquid anode (FLA-dc-APGD) modes. Design of experiments (DOE) and response surface methodology (RSM) were employed for the first time to optimize ReNPs synthesis. This included optimizing the concentration of ReO4- in ReNPs precursor solution, solution flow rate as well as discharge current. ReNPs were characterized using high-resolution transmission electron microscopy (HRTEM), dynamic light scattering (DLS), and X-Ray photoelectron spectroscopy (XPS). In turn, optical emission spectroscopy (OES) was employed for the identification of reactive species generated in plasma phase that contributed to the synthesis of ReNPs. The resultant sizes, surface charges, and phase compositions were linked with synthesis parameters and then with catalytic activities revealed by the variety of ReNPs. HRTEM photomicrographs revealed spherical and spherical-like morphologies of obtained ReNPs synthesized using FLC-dc-dc-APGD and FLA-dc-APGD modes with the actual sizes of 7.28 ± 2.90nm and 3.24 ± 0.57nm, respectively. Optimized conditions yielded ReNPs with exceptional catalytic activity, reducing 94.9% (FLC-dc-APGD) and 90.5% (FLA-dc-APGD) of 4-nitrophenol (4-NP) with the apparent rate constants (k1) 0.269 and 0.107min-1, respectively. Further, the conversions of 90% were achieved over FLC-dc-APGD-based ReNPs for nitrobenzene (NB), 2,4,6-trinitrophenol (2,4,6-TNP), 2,4-dinitrophenol (2,4-DNP), and 4-nitroaniline (4-NA). In these cases, the k1 values were 0.235, 0.174, 0.070, 0.001min-1 for, respectively. The results allowed to find a correlation between ReNP size distribution, oxidation state, and catalytic activity that suggested a potential for tailored Re nanocatalysts in environmental remediation.

Efficient peracetic acid activation by high-index facets of Cu2O under simulated solar light: The crucial role of uncoordinated Cu atoms

Tuning the facets of transition-metal catalysts to achieve effective micropollutant removal via peracetic acid (PAA) activation is a promising approach. However, within this process, the correlation between PAA activation and the atomic arrangement of the exposed facets is ambiguous. Herein, we present a comprehensive study wherein a series of Cu2O materials, with typical high-index facets ({211}, {311}, and {332}) and low-index facets ({100}, {110}, and {111}), were synthesized. These materials were used to investigate facet-dependent PAA activation for tetracycline (TC) degradation under simulated solar light irradiation. The results demonstrate that Cu2O with high-index {332} facets exhibit the optimal TC degradation (96.65 % within 20 min), and its kobs values are 1.52 and 2.01 times those of Cu2O with {311} and {211} facets, respectively. Detailed identification of the active species proved that •OH, 1O2, and the electron transfer process induced by the reactive Cu (I)–PAA* complexes were involved in TC degradation. In contrast to the {211} and {311} facets, PAA demonstrated a heightened tendency for adsorption and activation into active species on the {332} facets because of the denser uncoordinated Cu atoms. In addition, the facet heterojunction composed of {332} and {100} facets was conducive to the separation of photogenerated electron-hole pairs and charge migration, thus promoting the Cu(II)/Cu(I) cycle. In the practical applicability evaluation, Cu2O with {332} facets effectively removed multiple pollutants as well as actual pharmaceutical wastewater. This study provides a novel strategy for PAA activation by regulating the exposed facets of the catalyst.

Identification of pathogenic-like fungal species on Akebia trifoliata fruit by integrating transcriptome analysis and specific sequences of putative pathogens

Large-scale cultivation of recently domesticated crops poses great potential disease risk, so rapid and comprehensive identification of pathogenic microbes is of great significance and value for the commercial development of wild plant resources. Akebia trifoliata is widely cultivated in various regions of China, although its domestication remains in the early stages. Here, to avoid large economic losses, we identified the pathogenic-like fungi of widely cultivated A. trifoliata based on causal relationship between pathogens and hosts such as discernible symptoms, fungal diversity and differentially expressed sequences in symptomatic and asymptomatic fruits. First, we observed partly discernible symptoms of four diseases (powdery mildew, anthracnose, fruit shrinkage and brown spot) by observing disease development in the field. Second, comparative analysis of the ITS sequences between the symptomatic and asymptomatic rind bulks suggested that Cercospora, Colletotrichum and Strelitziana could contain pathogenic-like fungi. Finally, interaction transcriptome sequencing afforded strong evidence for 20 pathogenic-like fungi associated with five reported diseases in A. trifoliata and other plants and seven putative unknown diseases, among which the pathogenic-like fungi causing anthracnose, powdery mildew and brown spot were the three top richness fungi in symptomatic fruit rind. This study provides a new strategy for the rapid identification of pathogenic-like fungi in plants and provides some reference for farmers to prevent and control A. trifoliata diseases.

When aposematism is not enough: Exotic Rattus rattus shows no mercy for carcasses of Salamandra salamandra in insular populations.

Predator-prey interaction is a major force driving natural selection. Yet, the identification of species preying on, or consuming, aposematic species is largely unknown. Here, I conduct a study evaluating the role of the exotic Rattus rattus as a consumer and possible predator of the aposematic and toxic Salamandra salamandra. I used camera traps to investigate the response of R. rattus towards S. salamandra carcasses in two insular populations, Ons and San Martiño (NW Spain), which show remarkable contrasting behaviour (nocturnal vs. diurnal activity) and demographic and phenotypic differences. This study unveils R. rattus consumes S. salamandra despite its aposematic colour pattern and toxicity. The high number of salamander carcasses consumed or taken by rats throughout each island (90%-100%) and the lack of other possible predator-prey interactions points to R. rattus as an efficient consumer of S. salamandra in these insular environments, which might exert a high predation pressure on both islands. Yet, the drivers underlying the behavioural and phenotypic differences in these insular populations should be further investigated.

Taxonomic accuracy and complementarity between bulk and eDNA metabarcoding provides an alternative to morphology for biological assessment of freshwater macroinvertebrates

Determining biological status of freshwater ecosystems is critical for ensuring ecosystem health and maintaining associated services to such ecosystems. Freshwater macroinvertebrates respond predictably to environmental disturbances and are widely used in biomonitoring programs. However, many freshwater species are difficult to capture and sort from debris or substrate and morphological identification is challenging, especially larval stages, damaged specimens, or hyperdiverse groups such as Diptera. The advent of high throughput sequencing technologies has enhanced DNA barcoding tools to automatise species identification for whole communities, as metabarcoding is increasingly used to monitor biodiversity. However, recent comparisons have revealed little congruence between morphological and molecular-based identifications. Using broad range universal primers for DNA barcode marker cox1, we compare community composition captured between morphological and molecular-based approaches from different sources — tissue-based (bulk benthic and bulk drift samples) and environmental DNA (eDNA, filtered water) metabarcoding — for samples collected along a gradient of anthropogenic disturbances. For comparability, metabarcoding taxonomic assignments were filtered by taxa included in the standardised national biological metric IBMWP. At the family level, bulk benthic metabarcoding showed the highest congruence with morphology, and the most abundant taxa were captured by all techniques. Richness captured by morphology and bulk benthic metabarcoding decreased along the gradient, whereas richness recorded by eDNA remained constant and increased downstream when sequencing bulk drift. Estimates of biological metrics were higher using molecular than morphological identification. At species level, diversity captured by bulk benthic samples were higher than the other techniques. Importantly, bulk benthic and eDNA metabarcoding captured different and complementary portions of the community — benthic versus water column, respectively — and their combined use is recommended. While bulk benthic metabarcoding can likely replace morphology using similar benthic biological indices, water eDNA will require new metrics because this technique sequences a different portion of the community.

Weed species classification with UAV imagery and standard CNN models: Assessing the frontiers of training and inference phases

Accurate weed species identification is crucial for effective site-specific weed management (SSWM), enabling targeted and timely control measures for each weed in crop field. This study advanced the current approach to species-level weed identification during the early growth stage by integrating unmanned aerial vehicles (UAVs) imagery with standard convolutional neural networks (CNNs) models such as VGG16, Resnet152 and Inception-Resnet-v2. For this, a robust dataset was created with 33,467 labels of weeds (Atriplex patula, Chenopodium album, Convolvulus arvensis, Cyperus rotundus, Lolium rigidum, Portulaca oleracea, Salsola kali, Solanum nigrum) and crops (maize, tomato), which was subjected to different training, validation and test scenarios. Model inputs were adjusted in order to align them with the information represented by the UAV images. Initially, models were developed in balanced scenarios, gradually increasing label numbers to assess their performance. Inception-ResNet-v2 achieved over 90% accuracy with 400 labels, while ResNet152 and VGG16 required 600 and 800 labels, respectively, for similar accuracy. In a more complex and realistic scenarios with unbalanced datasets, Inception-ResNet-v2 outperformed, likely due to its deeper architecture and enhanced capability to capture intricate features and patterns within UAV images. The study emphasized the importance of the minority-to-majority species ratio in unbalanced datasets, which affects minority species classification. To prevent misclassification, it is crucial to determine the right number of labels for CNN model training and validation. Weed maps were generated after species classification using the Faster R–CNN algorithm as an object detector. This advancement in methodology facilitates the precise and efficient implementation of SSWM techniques.

Bat2Web: A Framework for Real-Time Classification of Bat Species Echolocation Signals Using Audio Sensor Data.

Bats play a pivotal role in maintaining ecological balance, and studying their behaviors offers vital insights into environmental health and aids in conservation efforts. Determining the presence of various bat species in an environment is essential for many bat studies. Specialized audio sensors can be used to record bat echolocation calls that can then be used to identify bat species. However, the complexity of bat calls presents a significant challenge, necessitating expert analysis and extensive time for accurate interpretation. Recent advances in neural networks can help identify bat species automatically from their echolocation calls. Such neural networks can be integrated into a complete end-to-end system that leverages recent internet of things (IoT) technologies with long-range, low-powered communication protocols to implement automated acoustical monitoring. This paper presents the design and implementation of such a system that uses a tiny neural network for interpreting sensor data derived from bat echolocation signals. A highly compact convolutional neural network (CNN) model was developed that demonstrated excellent performance in bat species identification, achieving an F1-score of 0.9578 and an accuracy rate of 97.5%. The neural network was deployed, and its performance was evaluated on various alternative edge devices, including the NVIDIA Jetson Nano and Google Coral.

Validation and redescription of Acanthamoeba terricola Pussard, 1964 (Amoebozoa: Acanthamoebidae)

Acanthamoeba castellanii (Douglas) Page, 1967 is the type species of a widespread genus of free-living amoebae, potentially pathogenic for humans and animals. The Neff strain is one of the most widely used in biological research, serving as a model for both A. castellanii and the whole genus in general. The Neff strain, isolated in California, closely resembles another strain found in France and originally described as a separate species, Acanthamoeba terricola Pussard, 1964, but both were successively synonymized with A. castellanii. Molecular sequence analysis has largely replaced morphological diagnosis for species identification in Acanthamoeba, and rDNA phylogenies show that the Neff strain forms a distinct lineage from that of the type strain of A. castellanii. In this study, we compared the type strain of A. terricola with the Neff strain and A. castellanii, and analysed the available molecular data including new sequences obtained from A. terricola. Here we provide molecular evidence to validate the species A. terricola. The Neff strain is therefore transferred to A. terricola and should no longer be considered as belonging to A. castellanii.

Habitat conditions and not moss composition mediate microbial community structure in Swiss peatlands.

Peatlands, one of the oldest ecosystems, globally store significant amounts of carbon and freshwater. However, they are under severe threat from human activities, leading to changes in water, nutrient and temperature regimes in these delicate systems. Such shifts can trigger a substantial carbon flux into the atmosphere and diminish the water-holding capacity of peatlands. Microbes associated with moss in peatlands play a crucial role in providing these ecosystem services, which are at risk due to global change. Therefore, understanding the factors influencing microbial composition and function is vital. Our study focused on five peatlands along an altitudinal gradient in Switzerland, where we sampled moss on hummocks containing Sarracenia purpurea. Structural equation modelling revealed that habitat condition was the primary predictor of community structure and directly influenced other environmental variables. Interestingly, the microbial composition was not linked to the local moss species identity. Instead, microbial communities varied significantly between sites due to differences in acidity levels and nitrogen availability. This finding was also mirrored in a co-occurrence network analysis, which displayed a distinct distribution of indicator species for acidity and nitrogen availability. Therefore, peatland conservation should take into account the critical habitat characteristics of moss-associated microbial communities.

Enhanced interannual drought resilience in mixed stands: unveiling possible complementarity effects between tree species of the Spanish Northern Plateau

AbstractClimate change is expected to intensify drought in the Mediterranean region. Previous studies indicate that tree species mixing may reduce the water stress. Our study investigates the response to past drought events of four co-occurring Mediterranean species: Pinus pinea L. (stone pine), Pinus pinaster Ait. (maritime pine), Juniperus thurifera L. (Spanish juniper) and Quercus ilex L (holm oak). The study was performed at an interannual scale, both in monospecific and mixed stands. Annual tree ring widths data measured on increment cores and stem discs obtained from 281 trees were used to quantify the responses to drought events using complementary resilience indices. Additionally, we assessed tree intra- and inter-specific competition impact over the past 25 years. We fitted and compared generalised linear mixed models to determine the influence of species identity, stand composition as intra-specific and inter-specific competition on complementary resilience indices and annual basal area increment. The co-existence with other species enhanced the resistance to drought of the stone pine as the resilience capacity of the Spanish juniper. Conversely, maritime pine’s drought resistance declined considerably in mixed stands. Notably, only the anisohydric species Spanish juniper and holm oak were able to return to pre-disturbance growth rates after the drought. The influence of competition on tree growth was found to differ according to the hydrological conditions of each year and varied based on the specific source of competition. Our study showed that mixed stands in the Spanish Northern Plateau, especially with holm oak and Spanish juniper, are more resilient to prolonged droughts due to spatio-temporal complementarity and subsequent competition reduction. That is another reason for which such composed mixed stands should be promoted in the arid conditions of the Spanish Northern Plateau.

Spatiotemporal variation in the gut microbiomes of co‐occurring wild rodent species

AbstractMammalian gut microbiomes differ within and among hosts. Hosts that occupy a broad range of environments may exhibit greater spatiotemporal variation in their microbiome than those constrained as specialists to narrower subsets of resources or habitats. This can occur if widespread host encounter a variety of ecological conditions that act to diversify their gut microbiomes and/or if generalized host species tend to form large populations that promote sharing and maintenance of diverse microbes. We studied spatiotemporal variation in the gut microbiomes of three co‐occurring rodent species across an environmental gradient in a Kenyan savanna. We hypothesized: (1) the taxonomic, phylogenetic, and functional compositions of gut microbiomes as predicted using the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) differ significantly among host species; (2) microbiome richness increases with population size for all host species; and (3) host species exhibit different levels of seasonal change in their gut microbiomes, reflecting different sensitivities to the environment. We evaluated changes in gut microbiome composition according to host species identity, site, and host population size using three years of capture–mark–recapture data and 351 microbiome samples. Host species differed significantly in microbiome composition, though the two species with more specialized diets and higher demographic sensitivities showed only slightly greater microbiome variability than those of a widespread dietary generalist. Total microbiome richness increased significantly with host population size for all species, but only one of the more specialized species also exhibited greater individual‐level microbiome richness in large populations. Across co‐occurring rodent species with diverse diets and life histories, large host population sizes were associated both with greater population‐level microbiome richness (sampling effects) and turnover in the relative abundance of bacterial taxa (environmental effects), but there was no consistent pattern for individual‐level richness (individual specialization). Together, our results show that maintenance of large host populations contributes to the maintenance of gut microbiome diversity in wild mammals.

Comparative chloroplast genomes of Argentina species: genome evolution and phylogenomic implications.

The genus Argentina Hill belongs to the tribe Potentilleae Sweet and contains approximately 75 species predominantly distributed in the Sino-Himalayan region and the Malesian archipelago. So far we have less knowledge on the phylogenetic relationships within Argentina owing to limited sampling of Argentina taxa or gene fragments in previous studies. Moreover, to date there is no phylogenetic study on Argentina from the perspective of comparative chloroplast (cp) genomics. Here we performed comparative genomic analyses on the cp genomes of 39 accessions representing 18 taxa of Argentina. The Argentina cp genomes presented the typical quadripartite structure, with the sizes ranging from 155 096 bp to 157 166 bp. The 39 Argentina cp genomes contained a set of 112 unique genes, comprising four ribosomal RNA (rRNA) genes, 30 transfer RNA (tRNA) genes, as well as 78 protein-coding genes (PCGs). The cp genome organization, gene content and order in Argentina were highly conserved, but some visible divergences were present in IR/SC boundary regions. Ten regions (trnH-GUG-psbA, trnG-GCC-trnfM-CAU, trnD-GUC-trnY-GUA, rpl32-trnL-UAG, atpH-atpI, rps16-trnQ-UUG, trnS-GCU-trnG-UCC, ndhF-rpl32, trnR-UCU-atpA, and accD-psaI) were identified as excellent candidate DNA markers for future studies on species identification, population genetics and phylogeny of Argentina. Our results indicated that Argentina is monophyletic. In the current sampling, the A. smithiana - A. anserina clade was sister to the remainder of Argentina. Our results corroborated the previous taxonomic treatments to transfer A. phanerophlebia and A. micropetala from the genus Sibbaldia L. to Argentina. Our results showed close relationships among A. stenophylla, A. microphylla, A. taliensis, and A. tatsienluensis, congruent with previous studies based on the morphology of these species. Twenty-six genes (rps3, rps15, rps16, rps19, rpl16, rpl20, rpl22, rpoA, rpoB, rpoC1, rpoC2, atpA, atpF, psbB, psbF, ndhA, ndhB, ndhC, ndhD, ndhF, rbcL, accD, ccsA, matK, ycf1, ycf2) were with sites under positive selection, and adaptive evolution of these genes might have played crucial roles in Argentina species adaptation to the harsh mountain environment. This study will facilitate future work on taxonomy, phylogenetics, and adaptive evolution of Argentina.

Exploration of mosses in urban-bogor habitats: Species identification, diversity and uniformity

This research focuses on the exploration of moss in the Bogor urban habitat, to explore the identification of moss types, measuring the level of diversity, and assessing the level of uniformity in the context of the urban environment. Data collection at the research location was divided into 3 stations with different environmental parameters. The method used in this research was an exploratory survey using the belt transect technique. The sampling method is purposive sampling with the help of a quadratic plot. The results of this research found 20 moss species identified on the green belt of Jalan Pajajaran, Bogor with a diversity index for the three stations respectively, namely 2.45; 2.02; and 1.78 which is classified into the medium category, and the uniformity index for the three stations respectively is 0.835; 0.814; 0.811 which is classified as high. These results show that the moss found can live by adapting to environmental factors in urban areas such as fluctuating temperature, humidity, and light intensity.

Epidemiology of rumen fluke infection in selected buffalo farms in perak, malaysia: prevalence, molecular species identification, and associated risk factors.

Rumen flukes cause heavy economic losses in the ruminant industry worldwide, especially in tropical and subtropical countries. This study estimated the prevalence of rumen flukes in buffaloes, identified the species diversity, and determined risk factors associated with rumen fluke prevalence in Perak, Peninsular Malaysia. A cross-sectional study was conducted, and 321 faecal samples were collected from six buffalo farms. A structured questionnaire was developed, and farmers were interviewed to obtain information regarding risk factors associated with rumen fluke infection. The faecal samples were examined using sedimentation and Flukefinder® techniques. Genomic DNA was extracted from the fluke eggs recovered using the Flukefinder® method, and the internal transcribed spacer 2 (ITS2) fragment was amplified and sequenced to facilitate species identification. The results showed that the overall prevalence of rumen fluke across the sampled farms was 40.2% (129/321). Three rumen fluke species were identified, namely, Fischoederius elongatus, F. cobboldi, and Orthocoelium streptocoelium. Several management factors had a significant association (P < 0.05) with rumen fluke prevalence, including production type, cleaning of the stable, drinking water system, flooding around the farm, grazing system, pasture sharing with other livestock, and deworming program. This work constitutes the first attempt to understand the epidemiology of rumen fluke infection in the region and suggests that good farm management, pasture management, choosing appropriate drugs, and proper husbandry practices may improve buffalo health and production in areas where rumen flukes are prevalent.

Medicinal Plant Identification using Machine Learning Algorithms

Medicinal Plant Identification using Machine Learning Algorithms

STUDY ON ANATOMICAL CHARATERIZATION OF MICROCOCCUS PANICULATA L

Micrococcus paniculata L., one of the important medicinal plants, commonly known as Cherikkotta, Kotta, Kottakka or Pottanga, of plant family Tiliaceae and are generally seen at the steep forested regions and also in scared grooves. The plant parts were utilized for the treatment of variety of diseases or conditions, including dysmenorrhea, paratyphoid, bone fractures, jaundice, kidney stones, dyspepsia, heat stroke, cold, fever, diarrhoea, hepatitis B, ingestion, and anthelmintic medication. It is widely distributed along the Western Ghats of India. Eventually, complete identification and authentication of plant material is needed to avoid confusion of species by non-taxonomist. Anatomical study supplement classical methods of identification. Specimen were examined by morphological and anatomical characteristics. Leaf and petiole anatomical profiling of this species Micrococcus paniculata occurring in of Kerala was investigated in this study. The study aims to search for the stable features marking out Micrococcus species. The species were distinguished based on the anatomical difference in the vascular bundles in midrib and petiole, palisade layer and type of stomata. The anatomical features of stem might be very useful for the identification of this plant species. Through this anatomical study, we concluded that this species has some unique features to its environmental habitat.

Harnessing the intragenomic variability of rRNA operons to improve differentiation of Vibrio species

Although the 16S rRNA gene is frequently used as a phylogenetic marker in analysis of environmental DNA, this marker often fails to distinguish closely related species, including those in the genus Vibrio. Here, we investigate whether inclusion and analysis of 23S rRNA sequence can help overcome the intrinsic weaknesses of 16S rRNA analyses for the differentiation of Vibrio species. We construct a maximum likelihood 16S rRNA gene tree to assess the use of this gene to identify clades of Vibrio species. Within the 16S rRNA tree, we identify the putative informative bases responsible for polyphyly, and demonstrate the association of these positions with tree topology. We demonstrate that concatenation of 16S and 23S rRNA genes increases the number of informative nucleotide positions, thereby overcoming ambiguities in 16S rRNA-based phylogenetic reconstructions. Finally, we experimentally demonstrate that this approach considerably improves the differentiation and identification of Vibrio species in environmental samples.

Detection of pathogenic bacteria in ticks from Isiolo and Kwale counties of Kenya using metagenomics.

Ticks are arachnid ectoparasites that rank second only to mosquitoes in the transmission of human diseases including bacteria responsible for anaplasmosis, ehrlichiosis, spotted fevers, and Lyme disease among other febrile illnesses. Due to the paucity of data on bacteria transmitted by ticks in Kenya, this study undertook a bacterial metagenomic-based characterization of ticks collected from Isiolo, a semi-arid pastoralist County in Eastern Kenya, and Kwale, a coastal County with a monsoon climate in the southern Kenyan border with Tanzania. A total of 2,918 ticks belonging to 3 genera and 10 species were pooled and screened in this study. Tick identification was confirmed through the sequencing of the Cytochrome C Oxidase Subunit 1 (COI) gene. Bacterial 16S rRNA gene PCR amplicons obtained from the above samples were sequenced using the MinION (Oxford Nanopore Technologies) platform. The resulting reads were demultiplexed in Porechop, followed by trimming and filtering in Trimmomatic before clustering using Qiime2-VSearch. A SILVA database pretrained naïve Bayes classifier was used to classify the Operational Taxonomic Units (OTUs) taxonomically. The bacteria of clinical interest detected in pooled tick assays were as follows: Rickettsia spp. 59.43% of pools, Coxiella burnetii 37.88%, Proteus mirabilis 5.08%, Cutibacterium acnes 6.08%, and Corynebacterium ulcerans 2.43%. These bacteria are responsible for spotted fevers, query fever (Q-fever), urinary tract infections, skin and soft tissue infections, eye infections, and diphtheria-like infections in humans, respectively. P. mirabilis, C. acnes, and C. ulcerans were detected only in Isiolo. Additionally, COI sequences allowed for the identification of Rickettsia and Coxiella species to strain levels in some of the pools. Diversity analysis revealed that the tick genera had high levels of Alpha diversity but the differences between the microbiomes of the three tick genera studied were not significant. The detection of C. acnes, commonly associated with human skin flora suggests that the ticks may have contact with humans potentially exposing them to bacterial infections. The findings in this study highlight the need for further investigation into the viability of these bacteria and the competency of ticks to transmit them. Clinicians in these high-risk areas also need to be appraised for them to include Rickettsial diseases and Q-fever as part of their differential diagnosis.

A new species of Naematelia (Tremellales, Basidiomycota) from India

A new species of Naematelia, N. encephaloidea, was collected and described from Silent Valley National Park, Kerala State, India. It is characterized by two types of swollen cells in trama, thick-walled, non-germinating, and thin-walled, germinating; thick-walled, globose conidia; inflated cells in the trama; lack of hyphidia. The identity of the new species is confirmed by morphological characteristics, and ITS and LSU sequence based molecular study. A key to the known Naematelia species is also provided.