The global landscape of immune-derived lncRNA signature in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a highly heterogeneous cancer. This heterogeneity has an impact on the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been found to play regulatory functions in cancer immunity. However, the global landscape of immune-derived lncRNA signatures has not yet been explored in colorectal cancer. METHODS: In this study, we applied DESeq2 to identify differentially expressed lncRNAs in colon cancer. Next, we performed an integrative analysis to globally identify immune-driven lncRNA markers in CRC, including immune-associated pathways, tumor immunogenomic features, tumor-infiltrating immune cells, immune checkpoints, microsatellite instability (MSI) and tumor mutation burden (TMB). RESULTS: We also identified dysregulated lncRNAs, such as LINC01354 and LINC02257, and their clinical relevance in CRC. Our findings revealed that the differentially expressed lncRNAs were closely associated with immune pathways. In addition, we found that RP11-354P11.3 and RP11-545G3.1 had the highest association with the immunogenomic signature. As a result, these signatures could serve as markers to assess immunogenomic activity in CRC. Among the immune cells, resting mast cells and M0 macrophages had the highest association with lncRNAs in CRC. The AC006129.2 gene was significantly associated with several immune checkpoints, for example, programmed cell death protein 1 (PD-1) and B and T lymphocyte attenuator (BTLA). Therefore, the AC006129.2 gene could be targeted to regulate the condition of immune cells or immune checkpoints to enhance the efficacy of immunotherapy in CRC patients. Finally, we identified 15 immune-related lncRNA-generated open reading frames (ORFs) corresponding to 15 cancer immune epitopes. CONCLUSION: In conclusion, we provided a genome-wide immune-driven lncRNA signature for CRC that might provide new insights into clinical applications and immunotherapy.

The gut microbial metabolite trimethylamine N-oxide and cardiovascular diseases.

Morbidity and mortality of cardiovascular diseases (CVDs) are exceedingly high worldwide. Researchers have found that the occurrence and development of CVDs are closely related to intestinal microecology. Imbalances in intestinal microecology caused by changes in the composition of the intestinal microbiota will eventually alter intestinal metabolites, thus transforming the host physiological state from healthy mode to pathological mode. Trimethylamine N-oxide (TMAO) is produced from the metabolism of dietary choline and L-carnitine by intestinal microbiota, and many studies have shown that this important product inhibits cholesterol metabolism, induces platelet aggregation and thrombosis, and promotes atherosclerosis. TMAO is directly or indirectly involved in the pathogenesis of CVDs and is an important risk factor affecting the occurrence and even prognosis of CVDs. This review presents the biological and chemical characteristics of TMAO, and the process of TMAO produced by gut microbiota. In particular, the review focuses on summarizing how the increase of gut microbial metabolite TMAO affects CVDs including atherosclerosis, heart failure, hypertension, arrhythmia, coronary artery disease, and other CVD-related diseases. Understanding the mechanism of how increases in TMAO promotes CVDs will potentially facilitate the identification and development of targeted therapy for CVDs.

Classification of Benign and Malignant Lung Nodules Based on Deep Convolutional Network Feature Extraction.

With the rapid development of detection technology, CT imaging technology has been widely used in the early clinical diagnosis of lung nodules. However, accurate assessment of the nature of the nodule remains a challenging task due to the subjective nature of the radiologist. With the increasing amount of publicly available lung image data, it has become possible to use convolutional neural networks for benign and malignant classification of lung nodules. However, as the network depth increases, network training methods based on gradient descent usually lead to gradient dispersion. Therefore, we propose a novel deep convolutional network approach to classify the benignity and malignancy of lung nodules. Firstly, we segmented, extracted, and performed zero-phase component analysis whitening on images of lung nodules. Then, a multilayer perceptron was introduced into the structure to construct a deep convolutional network. Finally, the minibatch stochastic gradient descent method with a momentum coefficient is used to fine-tune the deep convolutional network to avoid the gradient dispersion. The 750 lung nodules in the lung image database are used for experimental verification. Classification accuracy of the proposed method can reach 96.0%. The experimental results show that the proposed method can provide an objective and efficient aid to solve the problem of classifying benign and malignant lung nodules in medical images.

Comparative Analysis of Machine Learning Algorithms on Surface Enhanced Raman Spectra of Clinical Staphylococcus Species.

Raman spectroscopy (RS) is a widely used analytical technique based on the detection of molecular vibrations in a defined system, which generates Raman spectra that contain unique and highly resolved fingerprints of the system. However, the low intensity of normal Raman scattering effect greatly hinders its application. Recently, the newly emerged surface enhanced Raman spectroscopy (SERS) technique overcomes the problem by mixing metal nanoparticles such as gold and silver with samples, which greatly enhances signal intensity of Raman effects by orders of magnitudes when compared with regular RS. In clinical and research laboratories, SERS provides a great potential for fast, sensitive, label-free, and non-destructive microbial detection and identification with the assistance of appropriate machine learning (ML) algorithms. However, choosing an appropriate algorithm for a specific group of bacterial species remains challenging, because with the large volumes of data generated during SERS analysis not all algorithms could achieve a relatively high accuracy. In this study, we compared three unsupervised machine learning methods and 10 supervised machine learning methods, respectively, on 2,752 SERS spectra from 117 Staphylococcus strains belonging to nine clinically important Staphylococcus species in order to test the capacity of different machine learning methods for bacterial rapid differentiation and accurate prediction. According to the results, density-based spatial clustering of applications with noise (DBSCAN) showed the best clustering capacity (Rand index 0.9733) while convolutional neural network (CNN) topped all other supervised machine learning methods as the best model for predicting Staphylococcus species via SERS spectra (ACC 98.21%, AUC 99.93%). Taken together, this study shows that machine learning methods are capable of distinguishing closely related Staphylococcus species and therefore have great application potentials for bacterial pathogen diagnosis in clinical settings.

Atrial Arrhythmias in Patients with Severe COVID-19.

The number of confirmed COVID-19 cases has increased drastically; however, information regarding the impact of this disease on the occurrence of arrhythmias is scarce. The aim of this study was to determine the impact of COVID-19 on arrhythmia occurrence. This prospective study included patients with COVID-19 treated at the Leishenshan Temporary Hospital of Wuhan City, China, from February 24 to April 5, 2020. Demographic, comorbidity, and arrhythmias data were collected from patients with COVID-19 (n = 84) and compared with control data from patients with bacterial pneumonia (n = 84) infection. Furthermore, comparisons were made between patients with severe and nonsevere COVID-19 and between older and younger patients. Compared with patients with bacterial pneumonia, those with COVID-19 had higher total, mean, and minimum heart rates (all P < 0.01). Patients with severe COVID-19 (severe and critical type diseases) developed more atrial arrhythmias compared with those with nonsevere symptoms. Plasma creatine kinase isoenzyme (CKMB) levels (P=0.01) were higher in the severe group than in the nonsevere group, and there were more deaths in the severe group than in the nonsevere group (6 (15%) vs. 3 (2.30%); P=0.05). Premature atrial contractions (PAC) and nonsustained atrial tachycardia (NSAT) were significantly positively correlated with plasma CKMB levels but not with high-sensitive cardiac troponin I or myoglobin levels. Our data demonstrate that COVID-19 patients have higher total, mean, and minimum heart rates compared with those with bacterial pneumonia. Patients with severe or critical disease had more frequent atrial arrhythmias (including PAC and AF) and higher CKMB levels and mortality than those with nonsevere symptoms.

Glycogen Metabolism Impairment via Single Gene Mutation in the glgBXCAP Operon Alters the Survival Rate of Escherichia coli Under Various Environmental Stresses.

Glycogen is a highly branched polysaccharide that is widely present in all life domains. It has been identified in many bacterial species and functions as an important energy storage compound. In addition, it plays important roles in bacterial transmission, pathogenicity, and environmental viability. There are five essential enzymes (coding genes) directly involved in bacterial glycogen metabolism, which forms a single operon glgBXCAP with a suboperonic promoter in glgC gene in Escherichia coli. Currently, there is no comparative study of how the disruptions of the five glycogen metabolism genes influence bacterial phenotypes, such as growth rate, biofilm formation, and environmental survival, etc. In this study, we systematically and comparatively studied five E. coli single-gene mutants (ΔglgC, ΔglgA, ΔglgB, ΔglgP, ΔglgX) in terms of glycogen metabolism and explored their phenotype changes with a focus on environmental stress endurance, such as nutrient deprivation, low temperature, desiccation, and oxidation, etc. Biofilm formation in wild-type and mutant strains was also compared. E. coli wild-type stores the highest glycogen content after around 20-h culture while disruption of degradation genes (glgP, glgX) leads to continuous accumulation of glycogen. However, glycogen primary structure was abnormally changed in ΔglgP and ΔglgX. Meanwhile, increased accumulation of glycogen facilitates the growth of E. coli mutants but reduces glucose consumption in liquid culture and vice versa. Glycogen metabolism disruption also significantly and consistently increases biofilm formation in all the mutants. As for environmental stress endurance, glycogen over-accumulating mutants have enhanced starvation viability and reduced desiccation viability while all mutants showed decreased survival rate at low temperature. No consistent results were found for oxidative stress resistance in terms of glycogen metabolism disruptions, though ΔglgA shows highest resistance toward oxidation with unknown mechanisms. In sum, single gene disruptions in glgBXCAP operon significantly influence bacterial growth and glucose consumption during culture. Accumulation and structure of intracellular glycogen were also significantly altered. In addition, we observed significant changes in E. coli environmental viabilities due to the deletions of certain genes in the operon. Further investigations shall be focused on the molecular mechanisms behind these phenotype changes.

Comparative Transcriptome Profiling of Gaeumannomyces graminis var. tritici in Wheat Roots in the Absence and Presence of Biocontrol Bacillus velezensis CC09.

This study aimed to explore potential biocontrol mechanisms involved in the interference of antagonistic bacteria with fungal pathogenicity in planta. To do this, we conducted a comparative transcriptomic analysis of the "take-all" pathogenic fungus Gaeumannomyces graminis var. tritici (Ggt) by examining Ggt-infected wheat roots in the presence or absence of the biocontrol agent Bacillus velezensis CC09 (Bv) compared with Ggt grown on potato dextrose agar (PDA) plates. A total of 4,134 differentially expressed genes (DEGs) were identified in Ggt-infected wheat roots, while 2,011 DEGs were detected in Bv+Ggt-infected roots, relative to the Ggt grown on PDA plates. Moreover, 31 DEGs were identified between wheat roots, respectively infected with Ggt and Bv+Ggt, consisting of 29 downregulated genes coding for potential Ggt pathogenicity factors - e.g., para-nitrobenzyl esterase, cutinase 1 and catalase-3, and two upregulated genes coding for tyrosinase and a hypothetical protein in the Bv+Ggt-infected roots when compared with the Ggt-infected roots. In particular, the expression of one gene, encoding the ABA3 involved in the production of Ggt's hormone abscisic acid, was 4.11-fold lower in Ggt-infected roots with Bv than without Bv. This is the first experimental study to analyze the activity of Ggt transcriptomes in wheat roots exposed or not to a biocontrol bacterium. Our results therefore suggest the presence of Bv directly and/or indirectly impairs the pathogenicity of Ggt in wheat roots through complex regulatory mechanisms, such as hyphopodia formation, cell wall hydrolase, and expression of a papain inhibitor, among others, all which merit further investigation.

A Comparative Transcriptomic and Proteomic Analysis of Hexaploid Wheat's Responses to Colonization by Bacillus velezensis and Gaeumannomyces graminis, Both Separately and Combined.

Tritrophic interactions involving a biocontrol agent, a pathogen, and a plant have been analyzed predominantly from the perspective of the biocontrol agent. To explore the adaptive strategies of wheat in response to beneficial, pathogenic, and combined microorganisms, we performed the first comprehensive transcriptomic, proteomic, and biochemical analysis in wheat roots after exposure to Bacillus velezensis CC09, Gaeumannomyces graminis var. tritici, and their combined colonization, respectively. The transcriptional or translational programming of wheat roots inoculated with beneficial B. velezensis showed mild alterations compared with that of pathogenic G. graminis var. tritici. However, the combination of B. velezensis and G. graminis var. tritici activated a larger transcriptional or translational program than for each single microorganism, although the gene expression pattern was similar to that of individual infection by G. graminis var. tritici, suggesting a prioritization of defense against G. graminis var. tritici infection. Surprisingly, pathogen-associated molecular pattern-triggered immunity and effector-triggered immunity made wheat pretreated with B. velezensis more sensitive to subsequent G. graminis var. tritici infection. Additionally, B. velezensis triggered a salicylic acid (SA)-dependent mode of induced systemic resistance that resembles pathogen-induced systemic acquired resistance. Wheat plants mainly depend on SA-mediated resistance, and not that mediated by jasmonic acid (JA), against the necrotrophic pathogen G. graminis var. tritici. Moreover, SA-JA interactions resulted in antagonistic effects regardless of the type of microorganisms in wheat. Further enhancement of SA-dependent defense responses such as lignification to the combined infection was shown to reduce the level of induced JA-dependent defense against subsequent infection with G. graminis var. tritici. Altogether, our results demonstrate how the hexaploid monocot wheat responds to beneficial or pathogenic microorganisms and prolongs the onset of take-all disease through modulation of cell reprogramming and signaling events.

Bacillus velezensis CC09: A Potential 'Vaccine' for Controlling Wheat Diseases.

Biocontrol bacteria that can act like a "vaccine", stimulating plant resistance to pathogenic diseases, are still not fully elucidated. In this study, an endophytic bacterium, Bacillus velezensis CC09, labeled with green fluorescent protein, was tested for its colonization, migration, and expression of genes encoding iturin A synthetase within wheat tissues and organs as well as for protective effects against wheat take-all and spot blotch diseases. The results showed that strain CC09 not only formed biofilm on the root surface but was also widely distributed in almost every tissue, including the epidermis, cortex, and xylem vessels, and even migrated to stems and leaves, resulting in 66.67% disease-control efficacy (DCE) of take-all and 21.64% DCE of spot blotch. Moreover, the gene cluster encoding iturin A synthase under the control of the pitu promoter is expressed in B. velezensis CC09 in wheat tissues, which indicates that iturin A might contribute to the in-vivo antifungal activity and leads to the disease control. All these data suggested that strain CC09 can act like a 'vaccine' in the control of wheat diseases, with a single treatment inoculated on roots through multiple mechanisms.

Complete Genome Sequence of the Endophytic Biocontrol Strain Bacillus velezensis CC09.

Bacillus velezensis is a heterotypic synonym of B. methylotrophicus, B. amyloliquefaciens subsp. plantarum, and Bacillus oryzicola, and has been used to control plant fungal diseases. In order to fully understand the genetic basis of antimicrobial capacities, we did a complete genome sequencing of the endophytic B. velezensis strain CC09. Genes tightly associated with biocontrol ability, including nonribosomal peptide synthetases, polyketide synthetases, iron acquisition, colonization, and volatile organic compound synthesis were identified in the genome.

Species Diversity of Ramphogordius sanguineus/Lineus ruber-Like Nemerteans (Nemertea: Heteronemertea) and Geographic Distribution of R. sanguineus.

Heteronemerteans, such as Lineus ruber, L. viridis, Ramphogordius sanguineus, R. lacteus, Riseriellus occultus, and Micrura varicolor, share many similar external characters. Although several internal characters useful for distinguishing these nemertean species have been documented, their identification is based mostly on coloration, the shape of the head, and how they contract, which may not be always reliable. We sequenced the mitochondrial COI gene for 160 specimens recently collected from 27 locations around the world (provisionally identified as the above species, according to external characters and contraction patterns, with most of them as R. sanguineus). Based on these specimens, together with sequences of 16 specimens from GenBank, we conducted a DNA-based species delimitation/identification by means of statistical parsimony and phylogenetic analyses. Our results show that the analyzed specimens may contain nine species, which can be separated by large genetic gaps; heteronemerteans with an external appearance similar to R. sanguineus/Lineus ruber/L. viridis have high species diversity in European waters from where eight species can be discriminated. Our 42 individuals from Vancouver Island (Canada) are revealed to be R. sanguineus, which supports an earlier argument that nemerteans reported as L. ruber or L. viridis from the Pacific Northwest may refer to this species. We report R. sanguineus from Chile, southern China, and the species is also distributed on the Atlantic coast of South America (Argentina). In addition, present analyses reveal the occurrence of L. viridis in Qingdao, which is the first record of the species from Chinese waters.