Covalent docking in CDOCKER.

Targeted covalent inhibitors (TCIs) are considered to be an important component in the toolbox of drug discovery and about 30% of currently marketed drugs are TCIs. Although these drugs raise concerns about toxicity, their high potencies and prolonged effects result in less-frequent drug dosing and wide therapeutic margins for patients. This leads to increased interests in developing new computational methods to identify novel covalent inhibitors. The implementation of successful in silico docking algorithms have the potential to provide significant savings of time and money in the discovery of lead compounds. In this paper, we describe the implementation and testing of a covalent docking methodology in Rigid CDOCKER and the optimization of the corresponding physics-based scoring function with an additional customizable covalent bond grid potential which represents the free energy change of bond formation between the ligand and the receptor. We optimize the covalent bond grid potential for different common covalent bond formation reaction in TCIs. The average runtime for docking one covalent compound is 15 minutes which is comparable or faster than other well-established covalent docking methods. We demonstrate comparable top rank accuracy compared with other covalent docking algorithms using the pose prediction benchmark dataset for covalent docking algorithms developed by the Keseru group. Finally, we construct a retrospective virtual screening benchmark dataset containing 8 different receptor targets with different covalent bond formation reactions. To our knowledge, this is the largest dataset for benchmarking covalent docking methods. We show that our new covalent docking algorithm has the ability to identify lead compounds among a large chemical space. The largest AUC value is 0.909 for the target receptor CATK and the warhead chemistry of the covalent inhibitors is addition to the aldehyde functionality.

Morphological Characterization and Transcriptome Analysis of New Dwarf and Narrow-Leaf (dnl2) Mutant in Maize.

Lodging is the primary factor limiting high yield under a high plant density. However, an optimal plant height and leaf shape can effectively decrease the lodging risk. Here we studied an ethyl methanesulfonate (EMS)-induced dwarf and a narrow-leaf mutant, dnl2. Gene mapping indicated that the mutant was controlled by a gene located on chromosome nine. Phenotypic and cytological observations revealed that dnl2 showed inhibited cell growth, altered vascular bundle patterning, and disrupted secondary cell wall structure when compared with the wild-type, which could be the direct cause of the dwarf and narrow-leaf phenotype. The phytohormone levels, especially auxin and gibberellin, were significantly decreased in dnl2 compared to the wild-type plants. Transcriptome profiling of the internodes of the dnl2 mutant and wild-type revealed a large number of differentially expressed genes enriched in the cell wall biosynthesis, remodeling, and hormone biosynthesis and signaling pathways. Therefore, we suggest that crosstalk between hormones (the altered vascular bundle and secondary cell wall structure) may contribute to the dwarf and narrow-leaf phenotype by influencing cell growth. These results provide a foundation for DNL2 gene cloning and further elucidation of the molecular mechanism of the regulation of plant height and leaf shape in maize.

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy.

The binding of small-molecule ligands to protein or nucleic acid targets is important to numerous biological processes. Accurate prediction of the binding modes between a ligand and a macromolecule is of fundamental importance in structure-based structure-function exploration. When multiple ligands with different sizes are docked to a target receptor, it is reasonable to assume that the residues in the binding pocket may adopt alternative conformations upon interacting with the different ligands. In addition, it has been suggested that the entropic contribution to binding can be important. However, only a few attempts to include the side chain conformational entropy upon binding within the application of flexible receptor docking methodology exist. Here, we propose a new physics-based scoring function that includes both enthalpic and entropic contributions upon binding by considering the conformational variability of the flexible side chains within the ensemble of docked poses. We also describe a novel hybrid searching algorithm that combines both molecular dynamics (MD)-based simulated annealing and genetic algorithm crossovers to address the enhanced sampling of the increased search space. We demonstrate improved accuracy in flexible cross-docking experiments compared with rigid cross-docking. We test our developments by considering five protein targets, thrombin, dihydrofolate reductase(DHFR), T4 L99A, T4 L99A/M102Q, and PDE10A, which belong to different enzyme classes with different binding pocket environments, as a representative set of diverse ligands and receptors. Each target contains dozens of different ligands bound to the same binding pocket. We also demonstrate that this flexible docking algorithm may be applicable to RNA docking with a representative riboswitch example. Our findings show significant improvements in top ranking accuracy across this set, with the largest improvement relative to rigid, 23.64%, occurring for ligands binding to DHFR. We then evaluate the ability to identify lead compounds among a large chemical space for the proposed flexible receptor docking algorithm using a subset of the DUD-E containing receptor targets MCR, GCR, and ANDR. We demonstrate that our new algorithms show improved performance in modeling flexible binding site residues compared to DOCK. Finally, we select the T4 L99A and T4 L99A/M102Q decoy sets, containing dozens of binders and experimentally validated nonbinders, to test our approach in distinguishing binders from nonbinders. We illustrate that our new algorithms for searching and scoring have superior performance to rigid receptor CDOCKER as well as AutoDock Vina. Finally, we suggest that flexible CDOCKER is sufficiently fast to be utilized in high-throughput docking screens in the context of hierarchical approaches.

Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize.

Maize is the most important staple crop worldwide. Many of its agronomic traits present with a high level of heterosis. Combining ability was proposed to exploit the rule of heterosis, and general combining ability (GCA) is a crucial measure of parental performance. In this study, a recombinant inbred line population was used to construct testcross populations by crossing with four testers based on North Carolina design II. Six yield-relevant traits were investigated as phenotypic data. GCA effects were estimated for three scenarios based on the heterotic group and the number of tester lines. These estimates were then used to identify quantitative trait loci (QTL) and dissect genetic basis of GCA. A higher heritability of GCA was obtained for each trait. Thus, testing in early generation of breeding may effectively select candidate lines with relatively superior GCA performance. The GCA QTL detected in each scenario was slightly different according to the linkage mapping. Most of the GCA-relevant loci were simultaneously detected in all three datasets. Therefore, the genetic basis of GCA was nearly constant although discrepant inbred lines were appointed as testers. In addition, favorable alleles corresponding to GCA could be pyramided via marker-assisted selection and made available for maize hybrid breeding.

Fine Mapping and Identification of BnaC06.FtsH1, a Lethal Gene That Regulates the PSII Repair Cycle in Brassica napus.

Photosystem II (PSII) is an important component of the chloroplast. The PSII repair cycle is crucial for the relief of photoinhibition and may be advantageous when improving stress resistance and photosynthetic efficiency. Lethal genes are widely used in the efficiency detection and method improvement of gene editing. In the present study, we identified the naturally occurring lethal mutant 7-521Y with etiolated cotyledons in Brassica napus, controlled by double-recessive genes (named cyd1 and cyd2). By combining whole-genome resequencing and map-based cloning, CYD1 was fine-mapped to a 29 kb genomic region using 15,167 etiolated individuals. Through cosegregation analysis and functional verification of the transgene, BnaC06.FtsH1 was determined to be the target gene; it encodes an filamentation temperature sensitive protein H 1 (FtsH1) hydrolase that degrades damaged PSII D1 in Arabidopsis thaliana. The expression of BnaC06.FtsH1 was high in the cotyledons, leaves, and flowers of B. napus, and localized in the chloroplasts. In addition, the expression of EngA (upstream regulation gene of FtsH) increased and D1 decreased in 7-521Y. Double mutants of FtsH1 and FtsH5 were lethal in A. thaliana. Through phylogenetic analysis, the loss of FtsH5 was identified in Brassica, and the remaining FtsH1 was required for PSII repair cycle. CYD2 may be a homologous gene of FtsH1 on chromosome A07 of B. napus. Our study provides new insights into lethal mutants, the findings may help improve the efficiency of the PSII repair cycle and biomass accumulation in oilseed rape.

Genetic mapping and genomic selection for maize stalk strength.

BACKGROUND: Maize is one of the most important staple crops and is widely grown throughout the world. Stalk lodging can cause enormous yield losses in maize production. However, rind penetrometer resistance (RPR), which is recognized as a reliable measurement to evaluate stalk strength, has been shown to be efficient and useful for improving stalk lodging-resistance. Linkage mapping is an acknowledged approach for exploring the genetic architecture of target traits. In addition, genomic selection (GS) using whole genome markers enhances selection efficiency for genetically complex traits. In the present study, two recombinant inbred line (RIL) populations were utilized to dissect the genetic basis of RPR, which was evaluated in seven growth stages. RESULTS: The optimal stages to measure stalk strength are the silking phase and stages after silking. A total of 66 and 45 quantitative trait loci (QTL) were identified in each RIL population. Several potential candidate genes were predicted according to the maize gene annotation database and were closely associated with the biosynthesis of cell wall components. Moreover, analysis of gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway further indicated that genes related to cell wall formation were involved in the determination of RPR. In addition, a multivariate model of genomic selection efficiently improved the prediction accuracy relative to a univariate model and a model considering RPR-relevant loci as fixed effects. CONCLUSIONS: The genetic architecture of RPR is highly genetically complex. Multiple minor effect QTL are jointly involved in controlling phenotypic variation in RPR. Several pleiotropic QTL identified in multiple stages may contain reliable genes and can be used to develop functional markers for improving the selection efficiency of stalk strength. The application of genomic selection to RPR may be a promising approach to accelerate breeding process for improving stalk strength and enhancing lodging-resistance.

Transcriptome profiling and comparison of maize ear heterosis during the spikelet and floret differentiation stages.

BACKGROUND: Hybridization is a prominent process in the evolution of crop plants that can give rise to gene expression variation, phenotypic novelty and heterosis. Maize is the most successful crop in utilizing heterosis. The development of hybrid maize ears exhibits strong heterotic vigor and greatly affects maize yield. However, a comprehensive perspective on transcriptional variation and its correlation with heterosis during maize ear development is not available. RESULTS: Using RNA sequencing technology, we investigated the transcriptome profiles of maize ears in the spikelet and floret differentiation stages of hybrid ZD808 and its parents CL11 and NG5. Our results revealed that 53.9% (21,258) of maize protein-coding genes were transcribed in at least one genotype. In both development stages, significant numbers of genes were differentially expressed between the hybrid and its parents. Gene expression inheritance analysis revealed approximately 80% of genes were expressed additively, which suggested that the complementary effect may play a foundation role in maize ear heterosis. Among non-additively expressed genes, NG5-dominant genes were predominant. Analyses of the allele-specific gene expression in hybrid identified pervasive allelic imbalance and significant preferential expression of NG5 alleles in both developmental stages. The results implied that NG5 may provide beneficial alleles that contribute greatly to heterosis. Further comparison of parental and hybrid allele-specific expression suggested that gene expression variation is largely attributable to cis-regulatory variation in maize. The cis-regulatory variations tend to preserve the allelic expression levels in hybrid and result in additive expression. Comparison between the two development stages revealed that allele-specific expression and cis-/trans-regulatory variations responded differently to developmental cues, which may lead to stage-specific vigor phenotype during maize ear development. CONCLUSION: Our research suggests that cis-regulated additive expression may fine-tune gene expression level into an optimal status and play a foundation role in maize ear heterosis. Our work provides a comprehensive insight into transcriptional variation and its correlation with heterosis during maize ear development. The knowledge gained from this study presents novel opportunity to improve our maize varieties.

Genome-wide association analysis of forage quality in maize mature stalk.

BACKGROUND: Plant digestibility of silage maize (Zea mays L.) has a large influence on nutrition intake for animal feeding. Improving forage quality will enhance the utilization efficiency and feeding value of forage maize. Dissecting the genetic basis of forage quality will improve our understanding of the complex nature of cell wall biosynthesis and degradation, which is also helpful for breeding good quality silage maize. RESULTS: Acid detergent fiber (ADF), neutral detergent fiber (NDF) and in vitro dry matter digestibility (IVDMD) of stalk were evaluated in a diverse maize population, which is comprised of 368 inbred lines and planted across seven environments. Using a mixed model accounting for population structure and polygenic background effects, a genome-wide association study was conducted to identify single nucleotide polymorphisms (SNPs) significantly associated with forage quality. Scanning 559,285 SNPs across the whole genome, 73, 41 and 82 SNPs were found to be associated with ADF, NDF, and IVDMD, respectively. Each significant SNP explained 4.2 %-6.2 % of the phenotypic variation. Underlying these associated loci, 56 genes were proposed as candidate genes for forage quality. CONCLUSIONS: Of all the candidate genes proposed by GWAS, we only found a C3H gene (ZmC3H2) that is directly involved in cell wall component biosynthesis. The candidate genes found in this study are mainly involved in signal transduction, stress resistance, and transcriptional regulation of cell wall biosynthetic gene expression. Adding high digestibility maize into the association panel would be helpful for increasing genetic variability and identifying more genes associated with forage quality traits. Cloning and functional validation of these genes would be helpful for understanding the molecular mechanism of the fiber content and digestibility. These findings provide us new insights into cell wall formation and deposition.

Prolonged deficits in parvalbumin neuron stimulation-evoked network activity despite recovery of dendritic structure and excitability in the somatosensory cortex following global ischemia in mice.

Relatively few studies have examined plasticity of inhibitory neuronal networks following stroke in vivo, primarily due to the inability to selectively monitor inhibition. We assessed the structure of parvalbumin (PV) interneurons during a 5 min period of global ischemia and reperfusion in mice, which mimicked cerebral ischemia during cardiac arrest or forms of transient ischemic attack. The dendritic structure of PV-neurons in cortical superficial layers was rapidly swollen and beaded during global ischemia, but recovered within 5-10 min following reperfusion. Using optogenetics and a multichannel optrode, we investigated the function of PV-neurons in mouse forelimb somatosensory cortex. We demonstrated pharmacologically that PV-channelrhodopsin-2 (ChR2) stimulation evoked activation in layer IV/V, which resulted in rapid current sinks mediated by photocurrent and action potentials (a measure of PV-neuron excitability), which was then followed by current sources mediated by network GABAergic synaptic activity. During ischemic depolarization, the PV-ChR2-evoked current sinks (excitability) were suppressed, but recovered rapidly following reperfusion concurrent with repolarization of the DC-EEG. In contrast, the current sources reflecting GABAergic synaptic network activity recovered slowly and incompletely, and was coincident with the partial recovery of the forepaw stimulation-evoked current sinks in layer IV/V 30 min post reperfusion. Our in vivo data suggest that the excitability of PV inhibitory neurons was suppressed during global ischemia and rapidly recovered during reperfusion. In contrast, PV-ChR2 stimulation-evoked GABAergic synaptic network activity exhibited a prolonged suppression even ∼1 h after reperfusion, which could contribute to the dysfunction of sensation and cognition following transient global ischemia.

Stenotrophomonas maltophilia Isolated from the Gut Symbiotic Community of the Plastic-Eating Tenebrio molitor.

Polyvinyl chloride (PVC) waste is a major environmental challenge. In this study, we found that a PVC-eating insect, Tenebrio molitor, could survive by consuming PVC as a dietary supplement. To understand the gut symbiotic community, metagenomic analysis was performed to reveal the biodiversity of a symbiotic community in the midgut of Tenebrio molitor. Among them, seven genera were enriched from the midgut of the insect under culture conditions with PVC as carbon source. A strain of Stenotrophomonas maltophilia was isolated from the midgut symbiotic community of the plastic-eating Tenebrio molitor. To unravel the functional gene for the biodegradation enzyme, we sequenced the whole genome of Stenotrophomonas maltophilia and found that orf00390, annotated as a hydrolase, was highly expressed in the PVC culture niche.

Role of Microglial Mitophagy in Alleviating Postoperative Cognitive Dysfunction: a Mechanistic Study.

Postoperative cognitive dysfunction (POCD), a common complication following anesthesia and surgery, is influenced by hippocampal neuroinflammation and microglial activation. Mitophagy, a process regulating inflammatory responses by limiting the accumulation of damaged mitochondria, plays a significant role. This study aimed to determine whether regulating microglial mitophagy and the cGAS-STING pathway could alleviate cognitive decline after surgery. Exploratory laparotomy was performed to establish a POCD model using mice. Western blotting, immunofluorescence staining, transmission electron microscopy, and mt-Keima assays were used to examine microglial mitophagy and the cGAS-STING pathway. Quantitative polymerase chain reaction (qPCR) was used to detect inflammatory mediators and cytosolic mitochondrial DNA (mtDNA) levels in BV2 cells. Exploratory laparotomy triggered mitophagy and enhanced the cGAS-STING pathway in mice hippocampi. Pharmacological treatment reduced microglial activation, neuroinflammation, and cognitive impairment after surgery. Mitophagy suppressed the cGAS-STING pathway in mice hippocampi. In vitro, microglia-induced inflammation was mediated by mitophagy and the cGAS-STING pathway. Small interfering RNA (siRNA) of PINK1 hindered mitophagy activation and facilitated the cytosolic release of mtDNA, resulting in the initiation of the cGAS-STING pathway and innate immune response. Microglial mitophagy inhibited inflammatory responses via the mtDNA-cGAS-STING pathway inducing microglial mitophagy and inhibiting the mtDNA-cGAS-STING pathway may be an effective therapeutic approach for patients with POCD.

Identifying Artifacts from Large Library Docking.

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown the hit lists can become dominated by rare artifacts that cheat our scoring functions. Here, we investigate rescoring top-ranked docked molecules with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation as cross-filters. In retrospective studies, this approach deprioritized high-ranking nonbinders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against hits from docking against AmpC ß-lactamase. We prioritized 128 high-ranking molecules for synthesis and testing, a mixture of 39 molecules flagged as likely cheaters and 89 that were plausible inhibitors. None of the predicted cheating compounds inhibited AmpC detectably, while 57% of the 89 plausible compounds did so. As our libraries continue to grow, deprioritizing docking artifacts by rescoring with orthogonal methods may find wide use.

Identifying Artifacts from Large Library Docking.

While large library docking has discovered potent ligands for multiple targets, as the libraries have grown, the very top of the hit-lists can become populated with artifacts that cheat our scoring functions. Though these cheating molecules are rare, they become ever-more dominant with library growth. Here, we investigate rescoring top-ranked molecules from docking screens with orthogonal methods to identify these artifacts, exploring implicit solvent models and absolute binding free energy perturbation (AB-FEP) as cross-filters. In retrospective studies, this approach deprioritized high-ranking non-binders for nine targets while leaving true ligands relatively unaffected. We tested the method prospectively against results from large library docking AmpC ß-lactamase. From the very top of the docking hit lists, we prioritized 128 molecules for synthesis and experimental testing, a mixture of 39 molecules that rescoring flagged as likely cheaters and another 89 that were plausible true actives. None of the 39 predicted cheating compounds inhibited AmpC up to 200 µ M in enzyme assays, while 57% of the 89 plausible true actives did do so, with 19 of them inhibiting the enzyme with apparent K i values better than 50 µ M . As our libraries continue to grow, a strategy of catching docking artifacts by rescoring with orthogonal methods may find wide use in the field.

Defining context-dependent m6A RNA methylomes in Arabidopsis.

N6-Methyladenosine (m6A) prevalently occurs on cellular RNA across almost all kingdoms of life. It governs RNA fate and is essential for development and stress responses. However, the dynamic, context-dependent m6A methylomes across tissues and in response to various stimuli remain largely unknown in multicellular organisms. Here, we generate a comprehensive census that identifies m6A methylomes in 100 samples during development or following exposure to various external conditions in Arabidopsis thaliana. We demonstrate that m6A is a suitable biomarker to reflect the developmental lineage, and that various stimuli rapidly affect m6A methylomes that constitute the regulatory network required for an effective response to the stimuli. Integrative analyses of the census and its correlation with m6A regulators identify multiple layers of regulation on highly context-dependent m6A modification in response to diverse developmental and environmental stimuli, providing insights into m6A modification dynamics in the myriad contexts of multicellular organisms.

Recent advances in the plant epitranscriptome.

Chemical modifications of RNAs, known as the epitranscriptome, are emerging as widespread regulatory mechanisms underlying gene regulation. The field of epitranscriptomics advances recently due to improved transcriptome-wide sequencing strategies for mapping RNA modifications and intensive characterization of writers, erasers, and readers that deposit, remove, and recognize RNA modifications, respectively. Herein, we review recent advances in characterizing plant epitranscriptome and its regulatory mechanisms in post-transcriptional gene regulation and diverse physiological processes, with main emphasis on N6-methyladenosine (m6A) and 5-methylcytosine (m5C). We also discuss the potential and challenges for utilization of epitranscriptome editing in crop improvement.

pyCHARMM: Embedding CHARMM Functionality in a Python Framework.

CHARMM is rich in methodology and functionality as one of the first programs addressing problems of molecular dynamics and modeling of biological macromolecules and their partners, e.g., small molecule ligands. When combined with the highly developed CHARMM parameters for proteins, nucleic acids, small molecules, lipids, sugars, and other biologically relevant building blocks, and the versatile CHARMM scripting language, CHARMM has been a trendsetting platform for modeling studies of biological macromolecules. To further enhance the utility of accessing and using CHARMM functionality in increasingly complex workflows associated with modeling biological systems, we introduce pyCHARMM, Python bindings, functions, and modules to complement and extend the extensive set of modeling tools and methods already available in CHARMM. These include access to CHARMM function-generated variables associated with the system (psf), coordinates, velocities and forces, atom selection variables, and force field related parameters. The ability to augment CHARMM forces and energies with energy terms or methods derived from machine learning or other sources, written in Python, CUDA, or OpenCL and expressed as Python callable routines is introduced together with analogous functions callable during dynamics calculations. Integration of Python-based graphical engines for visualization of simulation models and results is also accessible. Loosely coupled parallelism is available for workflows such as free energy calculations, using MBAR/TI approaches or high-throughput multisite λ-dynamics (MSλD) free energy methods, string path optimization calculations, replica exchange, and molecular docking with a new Python-based CDOCKER module. CHARMM accelerated platform kernels through the CHARMM/OpenMM API, CHARMM/DOMDEC, and CHARMM/BLaDE API are also readily integrated into this Python framework. We anticipate that pyCHARMM will be a robust platform for the development of comprehensive and complex workflows utilizing Python and its extensive functionality as well as an optimal platform for users to learn molecular modeling methods and practices within a Python-friendly environment such as Jupyter Notebooks.

TMPRSS2 Inhibitor Discovery Facilitated through an In Silico and Biochemical Screening Platform.

The COVID-19 pandemic has highlighted the need for new antiviral approaches because many of the currently approved drugs have proven ineffective against mitigating SARS-CoV-2 infections. The host transmembrane serine protease TMPRSS2 is a promising antiviral target because it plays a role in priming the spike protein before viral entry occurs for the most virulent variants. Further, TMPRSS2 has no established physiological role, thereby increasing its attractiveness as a target for antiviral agents. Here, we utilize virtual screening to curate large libraries into a focused collection of potential inhibitors. Optimization of a recombinant expression and purification protocol for the TMPRSS2 peptidase domain facilitates subsequent biochemical screening and characterization of selected compounds from the curated collection in a kinetic assay. In doing so, we identify new noncovalent TMPRSS2 inhibitors that block SARS-CoV-2 infectivity in a cellular model. One such inhibitor, debrisoquine, has high ligand efficiency, and an initial structure-activity relationship study demonstrates that debrisoquine is a tractable hit compound for TMPRSS2.

Brassica evolution of essential BnaFtsH1 genes involved in the PSII repair cycle and loss of FtsH5.

The PSII repair cycle is an important part of photosynthesis and is essential for high photosynthetic efficiency. The study of essential genes in Brassica napus provides significant potential for the improvement of gene editing technology and molecular breeding design. Previously, we identified a B. napus lethal mutant (7-521Y), which was controlled by two recessive genes (cyd1 and cyd2). BnaC06.FtsH1 was identified as a CYD1 target gene through functional verification. In the present study, we employed fine-mapping, genetic complementation, and CRISPR/Cas9 experiments to identify BnaA07.FtsH1 as the target gene of CYD2, functioning similarly to BnaC06.FtsH1. By analyzing CRISPR/Cas9 T1 generation plants of the Westar variety, we found that the copy number of FtsH1 was positively correlated with its biomass accumulation. Transcriptome analysis of cotyledons revealed differences in the expression of photosynthesis antenna and structural proteins between the mutant and complementary seedlings. Phylogenetic and chromosome linear analyses, based on 15 sequenced cruciferous species, revealed that Brassica alone had lost FtsH5 during evolution. This may be related to the fact that FtsH5 was located at the end of chromosome ABK8 in the ancestor species. Cloning and identification of BnaFtsH1s provide a deeper understanding of PSII repair cycle mechanisms and offer new insights for the improvement of photosynthetic efficiency and molecular breeding design in B. napus.

Knockdown of Long Noncoding RNA 01124 Inhibits the Malignant Behaviors of Colon Cancer Cells via miR-654-5p/HAX-1.

Background: Previous studies have shown that long noncoding RNAs (lncRNAs) play a key role in cancer, including colon cancer (CC). However, the exact role of long noncoding RNA 01124 (LINC01124) in CC and its mechanisms of action remain unknown. In this study, we investigated the functional effects and the possible mechanism of LINC01124 in CC. Methods: We first determined the expression of LINC01124 in CC tissues (The Cancer Genome Atlas (TCGA) database) and cell lines (quantitative real-time polymerase chain reaction (qRT-PCR)). Functional analysis via Cell Counting Kit-8 (CCK-8), colony formation, cell cycle, wound healing and Transwell assays were performed, and a mechanistic experiment was performed with the western blotting. The function of LINC01124 was also determined in vivo using nude BALB/c mice. Results: The results showed that LINC01124 was upregulated in CC tissues and cell lines. Functional studies showed that knockdown of LINC01124 significantly suppressed the proliferation, migration, and invasion of colon cancer cells in vitro and in vivo. Subsequent mechanistic experiments indicated that LINC01124 acted as a sponge to suppress microRNA 654-5p, which targeted HAX-1. Downregulation of LINC01124 decreased the expression of HAX-1, and overexpression of the miR-654-5p inhibitor attenuated the sh-LINC01124-induced inhibition of CC cell proliferation, migration, and invasion. Conclusion: Collectively, this study revealed that the knockdown of LINC01124 inhibited the malignant behaviors of CC via the miR-654-5p/HAX-1 axis, suggesting that LINC01124 might be a therapeutic target for CC treatment.

CRMP5 regulates cell proliferation and development of colorectal cancer via MAPK-dependent signaling.

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Collapsin response mediator protein 5 (CRMP5) belongs to a family of five cytosolic proteins that serve a major role in neural development. CRMP5 has been identified as a biomarker of numerous cancer types, including lung cancer and glioblastoma. However, the role of CRMP5 in CRC remains unclear. In the present study, CRMP5 was characterized as a novel biomarker of poor survival in CRC. CRMP5-overexpression in CRC cells promoted cell proliferation and migration while CPMP5-knockdown decreased cell growth and migration. A novel mechanism was uncovered, by which CRMP5 regulates MAPK signaling to drive CRC cell proliferation and development. Furthermore, CRMP5-overexpression induced chemotherapy resistance and tumor recurrence in CRC. Taken together, these results demonstrated the important role of CRMP5 in the development and proliferation of CRC cells and suggested that CRMP5 may be a novel therapeutic target for CRC.