Camelus knoblochi genome reveals the complex evolutionary history of Old World camels.

Extant Old World camels (genus Camelus) contributed to the economic and cultural exchanges between the East and West for thousands of years.1,2 Although many remains have been unearthed,3,4,5 we know neither whether the prevalent hybridization observed between extant Camelus species2,6,7 also occurred between extinct lineages and the ancestors of extant Camelus species nor why some populations became extinct while others survived. To investigate these questions, we generated paleogenomic and stable isotope data from an extinct two-humped camel species, Camelus knoblochi. We find that in the mitochondrial phylogeny, all C. knoblochi form a paraphyletic group that nests within the diversity of modern, wild two-humped camels (Camelus ferus). In contrast, they are clearly distinguished from both wild and domesticated (Camelus bactrianus) two-humped camels on the nuclear level. Moreover, the divergence pattern of the three camel species approximates a trifurcation, because the most common topology is only slightly more frequent than the two other possible topologies. This mito-nuclear phylogenetic discordance likely arose due to interspecific gene flow between all three species, suggesting that interspecific hybridization is not exclusive to modern camels but a recurrent phenomenon throughout the evolutionary history of the genus Camelus. These results suggest that the genomic complexity of Old World camels' evolutionary history is underestimated when considering data from only modern species. Finally, we find that C. knoblochi populations began declining prior to the last glacial maximum and, by integrating palaeoecological evidence and stable isotope data, suggest that this was likely due to failure to adapt to a changing environment.

Transcriptome analysis of Kluyveromyces marxianus under succinic acid stress and development of robust strains.

Kluyveromyces marxianus has become an attractive non-conventional yeast cell factory due to its advantageous properties such as high thermal tolerance and rapid growth. Succinic acid (SA) is an important platform molecule that has been applied in various industries such as food, material, cosmetics, and pharmaceuticals. SA bioproduction may be compromised by its toxicity. Besides, metabolite-responsive promoters are known to be important for dynamic control of gene transcription. Therefore, studies on global gene transcription under various SA concentrations are of great importance. Here, comparative transcriptome changes of K. marxianus exposed to various concentrations of SA were analyzed. Enrichment and analysis of gene clusters revealed repression of the tricarboxylic acid cycle and glyoxylate cycle, also activation of the glycolysis pathway and genes related to ergosterol synthesis. Based on the analyses, potential SA-responsive promoters were investigated, among which the promoter strength of IMTCP2 and KLMA_50231 increased 43.4% and 154.7% in response to 15 g/L SA. In addition, overexpression of the transcription factors Gcr1, Upc2, and Ndt80 significantly increased growth under SA stress. Our results benefit understanding SA toxicity mechanisms and the development of robust yeast for organic acid production. KEY POINTS: • Global gene transcription of K. marxianus is changed by succinic acid (SA) • Promoter activities of IMTCP2 and KLMA_50123 are regulated by SA • Overexpression of Gcr1, Upc2, and Ndt80 enhanced SA tolerance.

Novel Roles of the Greatwall Kinase Rim15 in Yeast Oxidative Stress Tolerance through Mediating Antioxidant Systems and Transcriptional Regulation.

The Greatwall-family protein kinase Rim15 is associated with the nutrient starvation response, whereas its role in oxidative stress responses remains unclear. Here, acetic acid and peroxide were used as two oxidative stress elicitors. The antioxidant indicator assay under acetic acid stress revealed the impaired growth in rim15Δ related to the regulation of antioxidant systems. Comparative transcriptome analysis revealed that differentially expressed genes (DEGs) are predicted to be mostly regulated by oxidative stress-responsive transcriptional factor Yap1. Among the DEGs, acetic acid stress-induced genes were found, and YAP1 disruption also inhibited their induction. The deletion of Rim15 or the Rim15 kinase domain in yap1Δ did not further decrease the gene expression, suggesting that Rim15 functions together with Yap1 in regulating acetic acid stress-induced genes, which requires Rim15 kinase activity. Additionally, Rim15 regulated H2O2 stress tolerance through partially similar but special mechanisms in that Rim15 kinase activity impacted acetic acid and H2O2 stress tolerance in different degrees, indicating the different mechanisms underlying Rim15-mediated redox regulation against different stressors. These results benefit the better understanding of stress signaling pathways related to Rim15. Given that Rim15 and some of its target genes are conserved across eukaryotes, these results also provide a basis for studies of oxidative stress-related processes in other organisms.

Differential Protein Expression in Set5p-Mediated Acetic Acid Stress Response and Novel Targets for Engineering Yeast Stress Tolerance.

Acetic acid is a prevalent inhibitor in lignocellulosic hydrolysate, which represses microbial growth and bioproduction. Histone modification and chromatin remodeling have been revealed to be critical for regulating eukaryotic metabolism. However, related studies in chronic acetic acid stress responses remain unclear. Our previous studies revealed that overexpression of the histone H4 methyltransferase Set5p enhanced acetic acid stress tolerance of the budding yeast Saccharomyces cerevisiae. In this study, we examined the role of Set5p in acetic acid stress by analyzing global protein expression. Significant activation of intracellular protein expression under the stress was discovered, and the functions of the differential proteins were mainly involved in chromatin modification, signal transduction, and carbohydrate metabolism. Notably, a substantial increase of Set5p expression was observed in response to acetic acid stress. Functional studies demonstrated that the restriction of the telomere capping protein Rtc3p, as well as Ies3p and Taf14p, which are related to chromatin regulation, was critical for yeast stress response. This study enriches the understanding of the epigenetic regulatory mechanisms underlying yeast stress response mediated by histone-modifying enzymes. The results also benefit the development of robust yeast strains for lignocellulosic bioconversion.

Editorial for the Special Issue, 'Secondary Metabolites from Microorganisms or Microorganism-Host Interaction?'

In this Special Issue, there are 13 published papers from over 10 countries [...].

Regulatory Effects of Ganoderma lucidum, Grifola frondosa, and American ginseng Extract Formulation on Gut Microbiota and Fecal Metabolomics in Mice.

The bioactivities of Ganoderma lucidum, Grifola frondosa, and American ginseng have been extensively studied and documented. However, the effects of their complexes on the structural properties of intestinal microbiota and fecal metabolism remain unclear. Therefore, this paper aims to present a preliminary study to shed light on this aspect. In this study, an immunocompromised mouse model was induced using cyclophosphamide, and Ganoderma lucidum, Grifola frondosa, and American ginseng extract formulation (referred to as JGGA) were administered via gavage to investigate their modulatory effects on gut microbiota and fecal metabolism in mice. The effects of JGGA on immune enhancement were explored using serum test kits, hematoxylin-eosin staining, 16SrDNA high-throughput sequencing, and UHPLC-QE-MS metabolomics. The findings revealed potential mechanisms underlying the immune-enhancing effects of JGGA. Specifically, JGGA administration resulted in an improved body weight, thymic index, splenic index, carbon scavenging ability, hypersensitivity, and cellular inflammatory factor expression levels in mice. Further analysis demonstrated that JGGA reduced the abundance of Firmicutes, Proteobacteria, and Actinobacteria, while increasing the abundance of Bacteroidetes. Additionally, JGGA modulated the levels of 30 fecal metabolites. These results suggest that the immune enhancement observed with JGGA may be attributed to the targeted modulation of gut microbiota and fecal metabolism, thus promoting increased immunity in the body.

[Advances on the production of organic acids by yeast].

Organic acids are organic compounds that can be synthesized using biological systems. They often contain one or more low molecular weight acidic groups, such as carboxyl group and sulphonic group. Organic acids are widely used in food, agriculture, medicine, bio-based materials industry and other fields. Yeast has unique advantages of biosafety, strong stress resistance, wide substrate spectrum, convenient genetic transformation, and mature large-scale culture technology. Therefore, it is appealing to produce organic acids by yeast. However, challenges such as low concentration, many by-products and low fermentation efficiency still exist. With the development of yeast metabolic engineering and synthetic biology technology, rapid progress has been made in this field recently. Here we summarize the progress of biosynthesis of 11 organic acids by yeast. These organic acids include bulk carboxylic acids and high-value organic acids that can be produced naturally or heterologously. Finally, future prospects in this field were proposed.

Engineering yeast cell factories to produce biodegradable plastics and their monomers: Current status and prospects.

Traditional plastic products have caused serious environmental pollution due to difficulty to be degraded in the natural environment. In the recent years, biodegradable plastics are receiving increasing attention due to advantages in natural degradability and environmental friendliness. Biodegradable plastics have potential to be used in food, agriculture, industry, medicine and other fields. However, the high production cost of such plastics is the bottleneck that limits their commercialization and application. Yeasts, including budding yeast and non-conventional yeasts, are widely studied to produce biodegradable plastics and their organic acid monomers. Compared to bacteria, yeast strains are more tolerable to multiple stress conditions including low pH and high temperature, and also have other advantages such as generally regarded as safe, and no phage infection. In addition, synthetic biology and metabolic engineering of yeast have enabled its rapid and efficient engineering for bioproduction using various renewable feedstocks, especially lignocellulosic biomass. This review focuses on the recent progress in biosynthesis technology and strategies of monomeric organic acids for biodegradable polymers, including polylactic acid (PLA), polyhydroxyalkanoate (PHA), polybutylene succinate (PBS), and polybutylene adipate terephthalate (PBAT) using yeast cell factories. Improving the performance of yeast as a cell factory and strategies to improve yeast acid stress tolerance are also discussed. In addition, the critical challenges and future prospects for the production of biodegradable plastic monomer using yeast are also discussed.

Amentoflavone attenuates cell proliferation and induces ferroptosis in human gastric cancer by miR-496/ATF2 axis.

Amentoflavone (AF) is a natural multifunctional biflavonoid that has been revealed to possess multiple biological activities, including anticancer activity. Here, this work focused on exploring the functions and mechanism of AF in gastric cancer (GC). Levels of genes and proteins were examined by quantitative real-time PCR and western blotting. Cell proliferation and cell death were analyzed using cell counting kit-8, colony formation, and lactate dehydrogenase (LDH) release assay, respectively. Cell ferroptosis was evaluated by detecting the levels of malondialdehyde (MDA), reduced glutathione (GSH), Fe2+ , and intracellular reactive oxygen species (ROS). The binding between miR-496 and activating transcription factor 2 (ATF2) was confirmed by using dual-luciferase reporter assay. Murine xenograft assay was conducted for in vivo experiments. The results showed that AF suppressed the proliferation and induced ferroptotic cell death in GC cells. MiR-496 expression was decreased in GC tissues and cells, and AF treatment increased miR-496 expression level in GC cells. Functionally, miR-496 inhibition reversed the inhibitory effects of AF on GC cell proliferation and promoting effects on ferroptotic cell death. Mechanistically, ATF2 was targeted by miR-496. ATF2 expression was increased in GC tissues and cells, which was decreased by AF treatment and subsequently rescued by miR-496 downregulation in GC cells. Moreover, miR-496 overexpression suppressed the proliferation and induced ferroptotic cell death in GC cells via targeting ATF2. In all, AF suppressed the proliferation and induced ferroptotic cell death in GC cells via miR-496/ATF2 axis, indicating a novel therapeutic approach for GC patients.

Effectiveness and safety of mono-anlotinib mono therapy or in combination with chemotherapy in platinum-resistant recurrent ovarian cancer: a single-center retrospective study.

OBJECTIVE: To evaluate the clinical efficacy of mono-anlotinib therapy by itself or in combination with chemotherapy in platinum-resistant recurrent ovarian cancer (PROC). METHODS: The clinical data of 35 patients with platinum-resistant recurrent ovarian cancer admitted to the First Affiliated Hospital of Anhui Medical University from March 2019 to July 2020 were retrospectively analyzed. All the patients received anlotinib mono- or combined chemotherapy. The effectiveness and adverse events (AEs) were analyzed by RECIST1.1 and CTCAE5.0. RESULTS: In the 35 patients, the median follow-up was 9.80 (95% CI: 3.83-15.77) months. The median progression free survival (mPFS) achieved 6.50 (95% CI: 2.02-10.98) months, the objective response rate (ORR) achieved 17.14%, and disease control rate (DCR) achieved 60.00%. ORR and DCR were 12.50% and 25.0% for monotherapy, 18.52% and 70.37% for combined chemotherapy. The PFS of combined chemotherapy was longer than that of monotherapy (log-rank P = 0.003). thirty-four patients (97.14%) were in a third-line therapy or above, and their ORR and DCR were 14.71% and 58.82%, respectively. Two patients discontinued treatment because of intolerable AEs. No cases of grade 4-5 AEs have been reported. CONCLUSION: Anlotinib had promising effectiveness and tolerable safety in patients with PROC, even in patients who accepted anlotinib as a third-line or above therapy or with a history of other antiangiogenic drugs.

Analysis of Interpolation Methods in the Validation of Backscattering Coefficient Products.

Validation is the basis of synthetic aperture radar (SAR) image quantification applications. Based on the point target of the field site, the radiation characteristics of the backscattering coefficient image can be used to optimize the SAR imaging, and the product production system can be more closely targeted, to ensure the image product accuracy in the actual quantification application. In this study, the validation of the backscattering coefficient image was examined using calibrators, and the radiometric properties of the image were evaluated by extracting the radar cross-section of each point target. Bilinear interpolation and fast Fourier transform (FFT) interpolation methods were introduced for the local area interpolation of point targets, and the two methods were compared from the perspective of response function imaging and validation accuracy. The results show that the FFT interpolation method is more favorable for validating the backscattering coefficient.

Automatic Registration of Homogeneous and Cross-Source TomoSAR Point Clouds in Urban Areas.

Building reconstruction using high-resolution satellite-based synthetic SAR tomography (TomoSAR) is of great importance in urban planning and city modeling applications. However, since the imaging mode of SAR is side-by-side, the TomoSAR point cloud of a single orbit cannot achieve a complete observation of buildings. It is difficult for existing methods to extract the same features, as well as to use the overlap rate to achieve the alignment of the homologous TomoSAR point cloud and the cross-source TomoSAR point cloud. Therefore, this paper proposes a robust alignment method for TomoSAR point clouds in urban areas. First, noise points and outlier points are filtered by statistical filtering, and density of projection point (DoPP)-based projection is used to extract TomoSAR building point clouds and obtain the facade points for subsequent calculations based on density clustering. Subsequently, coarse alignment of source and target point clouds was performed using principal component analysis (PCA). Lastly, the rotation and translation coefficients were calculated using the angle of the normal vector of the opposite facade of the building and the distance of the outer end of the facade projection. The experimental results verify the feasibility and robustness of the proposed method. For the homologous TomoSAR point cloud, the experimental results show that the average rotation error of the proposed method was less than 0.1°, and the average translation error was less than 0.25 m. The alignment accuracy of the cross-source TomoSAR point cloud was evaluated for the defined angle and distance, whose values were less than 0.2° and 0.25 m.

Clptm1, a new target in suppressing epileptic seizure by regulating GABAA R-mediated inhibitory synaptic transmission in a PTZ-induced epilepsy model.

Disruption of gamma-amino butyric acid type A receptors (GABAA Rs) synaptic clustering and a decrease in the number of GABAA Rs in the plasma membrane are thought to contribute to alteration of the balance between excitatory and inhibitory neurotransmission, which promotes seizure induction and propagation. The multipass transmembrane protein cleft lip and palate transmembrane protein 1 (Clptm1) controls the forward trafficking of GABAA R, thus decaying miniature inhibitory postsynaptic current (mIPSC) of inhibitory synapses. In this study, using a pentylenetetrazol (PTZ)-induced epilepsy rat model, we found that Clptm1 regulates epileptic seizures by modulating GABAA R-mediated inhibitory synaptic transmission. First, we showed that Clptm1 expression was elevated in the PTZ-induced epileptic rats. Subsequently, we found that downregulation of Clptm1 expression protected against PTZ-induced seizures, which was attributed to an increase in the number of GABAA Rγ2s in the plasma membrane and the amplitude of mIPSC. Taken together, our findings identify a new anti-seizure target that provides a theoretical basis for the development of novel strategies for the prevention and treatment of epilepsy.

A novel damage identification method for flue gas turbine blades based on tip timing.

Tip timing signal analysis has been applied to the online condition monitoring of high-speed blades. However, traditional tip timing analysis methods are not suitable for low-speed flue gas turbines. Therefore, this paper proposes a novel blade tip timing signal analysis method based on an investigation of the dynamic response characteristics of low-speed blades. First, the finite element modal theory is introduced to analyze the characteristics of blade damage. Second, an equivalent cantilever beam analysis model of flue gas turbine blades is established under complex environment and working conditions. In order to monitor the variation of local stiffness, a damage identification method based on the variation of the free end deflection of the equivalent cantilever beam is proposed. Finally, a rotating blade tip timing monitoring testing rig is established to verify the feasibility of the proposed method. The results show that the cracks originating at about 80% of the blade height have the greatest influence on blade stiffness, followed by blade root. The calculated blade damage parameters are 4.8464 mm and 3.7588 mm, and the crack influencing factors are 4.7476 and 3.6822, respectively, indicating that the change trend is consistent with the blade damage rules.

Efficient Architecture Search for Continual Learning.

Continual learning with neural networks, which aims to learn a sequence of tasks, is an important learning framework in artificial intelligence (AI). However, it often confronts three challenges: 1) overcome the catastrophic forgetting problem; 2) adapt the current network to new tasks; and 3) control its model complexity. To reach these goals, we propose a novel approach named continual learning with efficient architecture search (CLEAS). CLEAS works closely with neural architecture search (NAS), which leverages reinforcement learning techniques to search for the best neural architecture that fits a new task. In particular, we design a neuron-level NAS controller that decides which old neurons from previous tasks should be reused (knowledge transfer) and which new neurons should be added (to learn new knowledge). Such a fine-grained controller allows finding a very concise architecture that can fit each new task well. Meanwhile, since we do not alter the weights of the reused neurons, we perfectly memorize the knowledge learned from the previous tasks. We evaluate CLEAS on numerous sequential classification tasks, and the results demonstrate that CLEAS outperforms other state-of-the-art alternative methods, achieving higher classification accuracy while using simpler neural architectures.

Genetic architecture of seed glycerolipids in Asian cultivated rice.

Glycerolipids are essential for rice development and grain quality but its genetic regulation remains unknown. Here we report its genetic base using metabolite-based genome-wide association study and metabolite-based quantitative traits locus (QTL) analyses based on lipidomic profiles of seeds from 587 Asian cultivated rice accessions and 103 chromosomal segment substitution lines, respectively. We found that two genes encoding phosphatidylcholine (PC):diacylglycerol cholinephosphotransferase (OsLP1) and granule-bound starch synthase I (Waxy) contribute to variations in saturated triacylglycerol (TAG) and lyso-PC contents, respectively. We demonstrated that allelic variation in OsLP1 sequence between indica and japonica results in different enzymatic preference for substrate PC-16:0/16:0 and different saturated TAG levels. Further evidence demonstrated that OsLP1 also affects heading date, and that co-selection of OsLP1 and a flooding-tolerant QTL in Aus results in the abundance of saturated TAGs associated with flooding tolerance. Moreover, we revealed that the sequence polymorphisms in Waxy has pleiotropic effects on lyso-PC and amylose content. We proposed that rice seed glycerolipids have been unintentionally shaped during natural and artificial selection for adaptive or import seed quality traits. Collectively, our findings provide valuable genetic resources for rice improvement and evolutionary insights into seed glycerolipid variations in rice.

Adversarial Human Trajectory Learning for Trip Recommendation.

The problem of trip recommendation has been extensively studied in recent years, by both researchers and practitioners. However, one of its key aspects-understanding human mobility-remains under-explored. Many of the proposed methods for trip modeling rely on empirical analysis of attributes associated with historical points-of-interest (POIs) and routes generated by tourists while attempting to also intertwine personal preferences-such as contextual topics, geospatial, and temporal aspects. However, the implicit transitional preferences and semantic sequential relationships among various POIs, along with the constraints implied by the starting point and destination of a particular trip, have not been fully exploited. Inspired by the recent advances in generative neural networks, in this work we propose DeepTrip-an end-to-end method for better understanding of the underlying human mobility and improved modeling of the POIs' transitional distribution in human moving patterns. DeepTrip consists of: a trip encoder (TE) to embed the contextual route into a latent variable with a recurrent neural network (RNN); and a trip decoder to reconstruct this route conditioned on an optimized latent space. Simultaneously, we define an Adversarial Net composed of a generator and critic, which generates a representation for a given query and uses a critic to distinguish the trip representation generated from TE and query representation obtained from Adversarial Net. DeepTrip enables regularizing the latent space and generalizing users' complex check-in preferences. We demonstrate, both theoretically and empirically, the effectiveness and efficiency of the proposed model, and the experimental evaluations show that DeepTrip outperforms the state-of-the-art baselines on various evaluation metrics.

Bacillamide F, Extracted from Marine Bacillus atrophaeus C89, Preliminary Effects on Leukemia Cell Lines.

Developing new treatments for leukemia is essential since current therapies often suffer from drug resistance and toxicity. Bacillamides are very promising, naturally occurring compounds with various bioactivities. In the present study, we investigated the use of bacillamide analogues, a new thiazole alkaloid bacillamide F that was isolated from marine Bacillus atrophaeus C89 associated with sponge Dysidea avara. The structure of the new compound bacillamide F with indolyl−thiazolyl−pyrrolidine ring was determined by high resolution mass spectrometry, secondary mass spectrometry, and nuclear magnetic resonance analyses. Intriguingly, bacillamide F is able to inhibit the proliferation of an acute myeloid leukemia cell line HL60 (IC50 (24 h) 21.82 µM), and an acute T-cell leukemia Jurkat (IC50 (24 h) 46.90 µM), rather than inhibit the proliferation of the acute histiocytic lymphoma U-937 cell line, human fetal lung fibroblast MRC-5 cell line, and some solid tumor cell lines (IC50 (24 h) > 100 µM). The study provides a new indication of the pharmacological activity of natural product bacillamides.

The cuproptosis-related gene signature serves as a potential prognostic predictor for ovarian cancer using bioinformatics analysis.

Background: Studies have shown that copper is involved in the tumorigenesis and development of ovarian cancer. In this work, we aimed to build a prognostic classification system associated with cuproptosis to predict ovarian cancer prognosis. Methods: Information of ovarian cancer samples were acquired from The Cancer Genome Atlas (TCGA)-ovarian cancer and GSE26193 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which were evaluated by tumor immune microenvironment analysis, TIDE algorithm, and functional enrichment analysis. Furthermore, limma analysis and univariate Cox analysis were used to construct a cuproptosis-related prognostic signature for ovarian cancer. Univariate and multivariate Cox regression analyses were used to analyze the independence of clinical factors and model. Results: A total of 15 genes related to cuproptosis were identified, and 2 clusters (C1 and C2) were determined. C1 had a better survival outcome, less advanced stage, enhanced immune infiltration, was more sensitive to immunotherapy, and showed enrichment in tricarboxylic acid (TCA)-related pathways. An 8 cuproptosis-associated gene signature was constructed, and the signature was verified in the GSE26193 dataset. A higher risk score of the cuproptosis-related gene signature was significantly correlated with worse overall survival (OS) (P<0.0001), which was validated in GSE26193 dataset successfully. Cox survival analysis showed that risk score was an independent predictor [hazard ratio (HR) =2.66, P<0.001]. Functional enrichment and tumor immune microenvironment analyses showed that high-risk patients tended to have immunologically sensitive tumors. Conclusions: The cuproptosis-related gene signature may serve as a potential prognostic predictor for ovarian cancer patients and may offer novel treatment strategies for ovarian cancer.

A Lightweight YOLOv5-MNE Algorithm for SAR Ship Detection.

Unlike optical satellites, synthetic aperture radar (SAR) satellites can operate all day and in all weather conditions, so they have a broad range of applications in the field of ocean monitoring. The ship targets' contour information from SAR images is often unclear, and the background is complicated due to the influence of sea clutter and proximity to land, leading to the accuracy problem of ship monitoring. Compared with traditional methods, deep learning has powerful data processing ability and feature extraction ability, but its complex model and calculations lead to a certain degree of difficulty. To solve this problem, we propose a lightweight YOLOV5-MNE, which significantly improves the training speed and reduces the running memory and number of model parameters and maintains a certain accuracy on a lager dataset. By redesigning the MNEBlock module and using CBR standard convolution to reduce computation, we integrated the CA (coordinate attention) mechanism to ensure better detection performance. We achieved 94.7% precision, a 2.2 M model size, and a 0.91 M parameter quantity on the SSDD dataset.