A unified classification system for HIV-1 5' long terminal repeats.

The HIV-1 provirus mainly consists of internal coding region flanked by 1 long terminal repeats (LTRs) at each terminus. The LTRs play important roles in HIV-1 reverse transcription, integration, and transcription. However, despite of the significant study advances of the internal coding regions of HIV-1 by using definite reference classification, there are no systematic and phylogenetic classifications for HIV-1 5' LTRs, which hinders our elaboration on 5' LTR and a better understanding of the viral origin, spread and therapy. Here, by analyzing all available resources of 5' LTR sequences in public databases following 4 recognized principles for the reference classification, 83 representatives and 14 consensus sequences were identified as representatives of 2 groups, 6 subtypes, 6 sub-subtypes, and 9 CRFs. To test the reliability of the supplemented classification system, the constructed references were applied to identify the 5' LTR assignment of the 22 clinical isolates in China. The results revealed that 16 out of 22 tested strains showed a consistent subtype classification with the previous LTR-independent classification system. However, 6 strains, for which recombination events within 5' LTR were demonstrated, unexpectedly showed a different subtype classification, leading a significant change of binding sites for important transcription factors including SP1, p53, and NF-κB. The binding change of these transcriptional factors would probably affect the transcriptional activity of 5' LTR. This study supplemented a unified classification system for HIV-1 5' LTRs, which will facilitate HIV-1 characterization and be helpful for both basic and clinical research fields.

Ecological niche shift and suitable area expansion of a globally invasive species Phthorimaea operculella.

Phthorimaea operculella is a major potato pest of global importance, early warning and detection of which are of significance. In this study, we analyzed the climate niche conservation of P. operculella during its invasion by comparing the overall climate niche from three dimensions, including the differences between native range (South America) and entire invaded region (excluding South America), the differences bwtween native range (South America) and five invaded continents (North America, Oceania, Asia, Africa, and Europe), as well as the differences between native region (South America) and an invaded region (China). We constructed ecological niche models for its native range (South America) and invaded region (China). The results showed that the climatic niche of the pest has expanded to varying degrees in different regions, indicating that the pest could well adapt to new environments during the invasion. Almost all areas of South America are suitable for P. operculella. In China, its suitable area is mainly concentrated in Shandong, Hebei, Tianjin, Beijing, Henan, Hubei, Yunnan, Guizhou, Sichuan, Hainan, northern Guangxi, southern Hunan, Anhui, Guangdong, Jiangsu, southern Shanxi, and southern Shaanxi. With increasing greenhouse gas emissions and global temperature, its suitable area will decrease at low latitude and increase gradually at high latitude. Specifically, the northern boundary will extend to Liaoning, Jilin, and the southeastern region of Inner Mongolia, while the western boundary extends to Sichuan and the southeast Qinghai-Tibet Plateau. The suitable area in the southeast Yunnan-Guizhou Plateau, Hainan Island, and the south of Yangtze River, will gradually decrease. The total suitable habitat area for P. operculella in China is projected to increase under future climate condition. From 2081 to 2100, under the three greenhouse gas emissions scenarios of ssp126, ssp370, and ssp585, the suitable area is expected to increase by 27.78, 165.54, and 140.41 hm2, respectively. Therefore, it is crucial to strengtehen vigilance and implement strict measures to prevent the further expansion of P. operculella.

Investigating the spatial distribution of volatile organic compounds in aircraft cabins from various emission sources.

Volatile organic compounds (VOCs) significantly affect the air quality in aircraft cabins, consequently affecting passenger health and comfort. Although VOC emission sources and their contributions have been studied extensively, the distribution characteristics of VOCs originating from diverse sources within cabins have received limited attention, and the correlation between VOC sources and concentrations in passenger breathing zones remains largely unexplored. To fill this knowledge gap, the concentration field of VOCs was investigated using a computational fluid dynamics model, and the results were experimentally validated in a typical single-aisle aircraft cabin with seven seat rows. The diffusion characteristics of different VOCs emitted by four typical sources in aircraft cabins (floors, human surfaces, seats, and respiratory sources) were analyzed and compared. The distribution of VOCs emitted by different sources was nonuniform and could be classified into two distinct categories. When the emission intensities of all sources were equal, the average concentration of VOCs emitted from the floor source were considerably lower in the passenger breathing zone (4.01 µg/m³) than those emitted from the human surface, seat, and respiratory sources, which exhibited approximately equal concentrations (6.82, 6.90, and 7.29 µg/m³, respectively). The analysis highlighted that the simplified lumped-parameter method could not accurately estimate the exposure concentrations within an aircraft cabin. To address this issue, we propose a correction method based on the emission intensity of each VOC source. This study provides critical insights into the diffusion characteristics of VOCs within aircraft cabins and VOC emissions from various sources.

Identification of Species by Combining Molecular and Morphological Data Using Convolutional Neural Networks.

Integrative taxonomy is central to modern taxonomy and systematic biology, including behavior, niche preference, distribution, morphological analysis, and DNA barcoding. However, decades of use demonstrate that these methods can face challenges when used in isolation, for instance, potential misidentifications due to phenotypic plasticity for morphological methods, and incorrect identifications because of introgression, incomplete lineage sorting, and horizontal gene transfer for DNA barcoding. Although researchers have advocated the use of integrative taxonomy, few detailed algorithms have been proposed. Here, we develop a convolutional neural network method (morphology-molecule network [MMNet]) that integrates morphological and molecular data for species identification. The newly proposed method (MMNet) worked better than four currently available alternative methods when tested with 10 independent data sets representing varying genetic diversity from different taxa. High accuracies were achieved for all groups, including beetles (98.1% of 123 species), butterflies (98.8% of 24 species), fishes (96.3% of 214 species), and moths (96.4% of 150 total species). Further, MMNet demonstrated a high degree of accuracy ($>$98%) in four data sets including closely related species from the same genus. The average accuracy of two modest subgenomic (single nucleotide polymorphism) data sets, comprising eight putative subspecies respectively, is 90%. Additional tests show that the success rate of species identification under this method most strongly depends on the amount of training data, and is robust to sequence length and image size. Analyses on the contribution of different data types (image vs. gene) indicate that both morphological and genetic data are important to the model, and that genetic data contribute slightly more. The approaches developed here serve as a foundation for the future integration of multimodal information for integrative taxonomy, such as image, audio, video, 3D scanning, and biosensor data, to characterize organisms more comprehensively as a basis for improved investigation, monitoring, and conservation of biodiversity. [Convolutional neural network; deep learning; integrative taxonomy; single nucleotide polymorphism; species identification.].

Efficient COI barcoding using high throughput single-end 400 bp sequencing.

BACKGROUND: Over the last decade, the rapid development of high-throughput sequencing platforms has accelerated species description and assisted morphological classification through DNA barcoding. However, the current high-throughput DNA barcoding methods cannot obtain full-length barcode sequences due to read length limitations (e.g. a maximum read length of 300 bp for the Illumina's MiSeq system), or are hindered by a relatively high cost or low sequencing output (e.g. a maximum number of eight million reads per cell for the PacBio's SEQUEL II system). RESULTS: Pooled cytochrome c oxidase subunit I (COI) barcodes from individual specimens were sequenced on the MGISEQ-2000 platform using the single-end 400 bp (SE400) module. We present a bioinformatic pipeline, HIFI-SE, that takes reads generated from the 5' and 3' ends of the COI barcode region and assembles them into full-length barcodes. HIFI-SE is written in Python and includes four function modules of filter, assign, assembly and taxonomy. We applied the HIFI-SE to a set of 845 samples (30 marine invertebrates, 815 insects) and delivered a total of 747 fully assembled COI barcodes as well as 70 Wolbachia and fungi symbionts. Compared to their corresponding Sanger sequences (72 sequences available), nearly all samples (71/72) were correctly and accurately assembled, including 46 samples that had a similarity score of 100% and 25 of ca. 99%. CONCLUSIONS: The HIFI-SE pipeline represents an efficient way to produce standard full-length barcodes, while the reasonable cost and high sensitivity of our method can contribute considerably more DNA barcodes under the same budget. Our method thereby advances DNA-based species identification from diverse ecosystems and increases the number of relevant applications.

Regional assemblages shaped by historical and contemporary factors: Evidence from a species-rich insect group.

Understanding diversity patterns requires accounting for the roles of both historical and contemporary factors in the assembly of communities. Here, we compared diversity patterns of two moth assemblages sampled from Taihang and Yanshan mountains in Northern China and performed ancestral range reconstructions using the Multi-State Speciation and Extinction model, to track the origins of these patterns. Further, we estimated diversification rates of the two moth assemblages and explored the effects of contemporary ecological factors. From 7,788 specimens we identified 835 species belonging to 23 families, using both DNA barcode analysis and morphology. Moths in Yanshan mountains showed higher species diversity than in Taihang mountains. Ancestral range analysis indicated Yanshan as the origin, with significant historical dispersals from Yanshan to Taihang. Asymmetrical diversification, population expansion, along with frequent and considerable gene flow were detected between communities. Moreover, dispersal limitation or the joint effect of environment filtering and dispersal limitation were inferred as main driving forces shaping current diversity patterns. In summary, we demonstrate that a multiscale (community, population and species level) analysis incorporating both historical and contemporary factors can be useful in delineating factors contributing to community assembly and patterning in diversity.

FuzzyID2: A software package for large data set species identification via barcoding and metabarcoding using hidden Markov models and fuzzy set methods.

Species identification through DNA barcoding or metabarcoding has become a key approach for biodiversity evaluation and ecological studies. However, the rapid accumulation of barcoding data has created some difficulties: for instance, global enquiries to a large reference library can take a very long time. We here devise a two-step searching strategy to speed identification procedures of such queries. This firstly uses a Hidden Markov Model (HMM) algorithm to narrow the searching scope to genus level and then determines the corresponding species using minimum genetic distance. Moreover, using a fuzzy membership function, our approach also estimates the credibility of assignment results for each query. To perform this task, we developed a new software pipeline, FuzzyID2, using Python and C++. Performance of the new method was assessed using eight empirical data sets ranging from 70 to 234,535 barcodes. Five data sets (four animal, one plant) deployed the conventional barcode approach, one used metabarcodes, and two were eDNA-based. The results showed mean accuracies of generic and species identification of 98.60% (with a minimum of 95.00% and a maximum of 100.00%) and 94.17% (with a range of 84.40%-100.00%), respectively. Tests with simulated NGS sequences based on realistic eDNA and metabarcode data demonstrated that FuzzyID2 achieved a significantly higher identification success rate than the commonly used Blast method, and the TIPP method tends to find many fewer species than either FuzztID2 or Blast. Furthermore, data sets with tens of thousands of barcodes need only a few seconds for each query assignment using FuzzyID2. Our approach provides an efficient and accurate species identification protocol for biodiversity-related projects with large DNA sequence data sets.

Person to person droplets transmission characteristics in unidirectional ventilated protective isolation room: The impact of initial droplet size.

Person to person droplets/particles or contaminant cross transmission is an important issue in ventilated environment, especially in the unidirectional ventilated protective isolation room (UVPIR) where the patient's immune system is extremely low and easily infected. We simulated the dispersion process of the droplets with initial diameter of 100 µm, 10 µm and gaseous contaminant in unidirectional ventilated protective isolation room and studied the droplets dispersion and cross transmission with different sizes. The droplets with initial size of 100 µm settle out of the coughing jet quickly after coming out from mouth and cannot be carried by the coughing jet to the human thermal plume affecting (HTPA) zone of the susceptible manikin. Hence, the larger droplets disperse mainly in the HTPA zone of the source manikin, and the droplets cross transmission between source manikin and susceptible manikin is very small. The droplets with initial size of 10 µm and gaseous contaminant have similar dispersion but different removal process in the UVPIR. Part of the droplets with initial size of 10 µm and gaseous contaminant that are carried by the higher velocity coughing airflow can enter the HTPA zone of the susceptible manikin and disperse around it. The other part cannot spread to the susceptible manikin's HTPA zone and mainly spread in the source manikin's HTPA zone. The results from this study would be useful for UVPIR usage and operation in order to minimize the risk of cross infection.