STAR Protoc. 2021 Mar 17;2(2):100398. doi: 10.1016/j.xpro.2021.100398. eCollection 2021 Jun 18.

ABSTRACT

RNA in situ hybridization can be time-consuming and difficult to troubleshoot. Here, we provide an optimized protocol for maize leaf tissue, though it can be applied to other plant tissues such as shoot apical meristems, embryos, and floral organs. We generate three >100 bp unique antisense probes for each gene of interest and hybridize them to tissue sections. For complete details on the use and execution of this protocol, please refer to Bezrutczyk et al. (2021).

PMID:33796873 | PMC:PMC7995656 | DOI:10.1016/j.xpro.2021.100398

Nat Cancer. 2020 Nov;1(11):1113-1127. doi: 10.1038/s43018-020-00124-1. Epub 2020 Oct 19.

ABSTRACT

Multi-agent combination chemotherapy can be curative in acute lymphoblastic leukemia (ALL). Still, patients with primary refractory disease or with relapsed leukemia have a very poor prognosis. Here we integrate an in-depth dissection of the mutational landscape across diagnostic and relapsed pediatric and adult ALL samples with genome-wide CRISPR screen analysis of gene-drug interactions across seven ALL chemotherapy drugs. By combining these analyses, we uncover diagnostic and relapse-specific mutational mechanisms as well as genetic drivers of chemoresistance. Functionally, our data identifies common and drug-specific pathways modulating chemotherapy response and underscores the effect of drug combinations in restricting the selection of resistance-driving genetic lesions. In addition, by identifying actionable targets for the reversal of chemotherapy resistance, these analyses open novel therapeutic opportunities for the treatment of relapse and refractory disease.

PMID:33796864 | PMC:PMC8011577 | DOI:10.1038/s43018-020-00124-1

Nat Mach Intell. 2021 Feb;3(2):172-180. doi: 10.1038/s42256-020-00282-y. Epub 2021 Jan 18.

ABSTRACT

Transcription factors (TFs) bind DNA by recognizing specific sequence motifs, typically of length 6-12bp. A motif can occur many thousands of times in the human genome, but only a subset of those sites are actually bound. Here we present a machine learning framework leveraging existing convolutional neural network architectures and model interpretation techniques to identify and interpret sequence context features most important for predicting whether a particular motif instance will be bound. We apply our framework to predict binding at motifs for 38 TFs in a lymphoblastoid cell line, score the importance of context sequences at base-pair resolution, and characterize context features most predictive of binding. We find that the choice of training data heavily influences classification accuracy and the relative importance of features such as open chromatin. Overall, our framework enables novel insights into features predictive of TF binding and is likely to inform future deep learning applications to interpret non-coding genetic variants.

PMID:33796819 | PMC:PMC8009085 | DOI:10.1038/s42256-020-00282-y

Mitochondrial DNA B Resour. 2021 Mar 24;6(3):1012-1013. doi: 10.1080/23802359.2021.1894998.

ABSTRACT

Viola philippica, as a traditional Chinese medicine, has great value in treating various diseases. Here, we report the chloroplast genome of V. philippica and its phylogenetic feature. The complete chloroplast genome is 156,744 bp in length, assembled from 22,346,570 reads, and its GC contents ratio is 36.26%. Its long single-copy (LSC) region is 85,892 bp. The small single-copy (SSC) region covers 18,006 bp and inverted repeat (IR) is 26,423 bp. It encodes 77 genes, including 43 protein genes, 4 rRNA genes, and 30 tRNA genes. Moreover, according to the phylogenetic analysis for a total of 12 chloroplast sequences, V. philippica demonstrated close relationship within genus Viola.

PMID:33796720 | PMC:PMC7995846 | DOI:10.1080/23802359.2021.1894998

Mitochondrial DNA B Resour. 2021 Mar 18;6(3):1009-1011. doi: 10.1080/23802359.2021.1894997.

ABSTRACT

The marbled polecat, Vormela peregusna, is one of the least studied species in the Mustelidae family, especially with regard to phylogeography and genetic diversity. In this study, we determined the mitochondrial genome sequence of V. peregusna and investigated its position within the Mustelidae phylogeny. The generated mitogenome is 15,982 bp in length; it consists of 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and a control region.

PMID:33796719 | PMC:PMC7995864 | DOI:10.1080/23802359.2021.1894997

Mitochondrial DNA B Resour. 2021 Mar 15;6(3):883-885. doi: 10.1080/23802359.2021.1886012.

ABSTRACT

The Caucasian Squirrel, Sciurus anomalus, is the only representative of the Sciuridae family in the Eastern Mediterranean region. In this study, the mitochondrial genome of the Sciurus anomalus species was generated, and we investigate its phylogenetic position within the Sciuridae family. The generated mitogenome sequence is 16,234 bp. It is composed of a control region and a conserved set of 37 genes containing 13 protein-coding genes, 22 tRNA genes and 2 rRNA genes.

PMID:33796667 | PMC:PMC7971277 | DOI:10.1080/23802359.2021.1886012

Mitochondrial DNA B Resour. 2021 Mar 15;6(3):878-879. doi: 10.1080/23802359.2021.1886010.

ABSTRACT

We report the first mitochondrial genome of the Antarctic microalga Micractinium simplicissimum KSF0127. The circular mitochondrial genome was 67,923 bp in length and contained 45 protein-coding genes, one ribosomal RNA gene, and 60 transfer RNA genes. The phylogenetic tree was constructed with eight previously reported mitogenome sequences and showed the phylogenetic position of M. simplicissimum KSF0127 within the Chlorellaceae family.

PMID:33796665 | PMC:PMC7971331 | DOI:10.1080/23802359.2021.1886010

Front Bioeng Biotechnol. 2021 Mar 16;9:642023. doi: 10.3389/fbioe.2021.642023. eCollection 2021.

ABSTRACT

Crude glycerol has emerged as a suitable feedstock for the biotechnological production of various industrial chemicals given its high surplus catalyzed by the biodiesel industry. Pseudomonas bacteria metabolize the polyol into several biopolymers, including alginate and medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHAs). Although P. putida is a suited platform to derive these polyoxoesters from crude glycerol, the attained concentrations in batch and fed-batch cultures are still low. In this study, we employed P. putida KT2440 and the hyper-PHA producer ΔphaZ mutant in two different fed-batch modes to synthesize mcl-PHAs from raw glycerol. Initially, the cells grew in a batch phase (μ max 0.21 h-1) for 22 h followed by a carbon-limiting exponential feeding, where the specific growth rate was set at 0.1 (h-1), resulting in a cell dry weight (CDW) of nearly 50 (g L-1) at 40 h cultivation. During the PHA production stage, we supplied the substrate at a constant rate of 50 (g h-1), where the KT2440 and the ΔphaZ produced 9.7 and 12.7 gPHA L-1, respectively, after 60 h cultivation. We next evaluated the PHA production ability of the P. putida strains using a DO-stat approach under nitrogen depletion. Citric acid was the main by-product secreted by the cells, accumulating in the culture broth up to 48 (g L-1) under nitrogen limitation. The mutant ΔphaZ amassed 38.9% of the CDW as mcl-PHA and exhibited a specific PHA volumetric productivity of 0.34 (g L-1 h-1), 48% higher than the parental KT2440 under the same growth conditions. The biosynthesized mcl-PHAs had average molecular weights ranging from 460 to 505 KDa and a polydispersity index (PDI) of 2.4-2.6. Here, we demonstrated that the DO-stat feeding approach in high cell density cultures enables the high yield production of mcl-PHA in P. putida strains using the industrial crude glycerol, where the fed-batch process selection is essential to exploit the superior biopolymer production hallmarks of engineered bacterial strains.

PMID:33796510 | PMC:PMC8007980 | DOI:10.3389/fbioe.2021.642023

Oncotarget. 2021 Mar 16;12(6):525-533. doi: 10.18632/oncotarget.27901. eCollection 2021 Mar 16.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC), the most common histological subtype of pancreatic cancer, has one of the highest case fatality rates of all known solid malignancies. Over the past decade, several landmark studies have established mutations in KRAS and TP53 as the predominant drivers of PDAC pathogenesis and therapeutic resistance, though treatment options for PDACs and other tumors with these mutations remain extremely limited. Hampered by late tumor discovery and diagnosis, clinicians are often faced with using aggressive and non-specific chemotherapies to treat advanced disease. Clinically meaningful responses to targeted therapy are often limited to the minority of patients with susceptible PDACs, and immunotherapies have routinely encountered roadblocks in effective activation of tumor-infiltrating immune cells. Alternative RNA splicing (ARS) has recently gained traction in the PDAC literature as a field from which we may better understand and treat complex mechanisms of PDAC initiation, progression, and therapeutic resistance. Here, we review PDAC pathogenesis as it relates to fundamental ARS biology, with an extension to implications for PDAC patient clinical management.

PMID:33796221 | PMC:PMC7984828 | DOI:10.18632/oncotarget.27901

Front Neuroinform. 2021 Mar 16;15:561012. doi: 10.3389/fninf.2021.561012. eCollection 2021.

ABSTRACT

As multielectrode array technology increases in popularity, accessible analytical tools become necessary. Simultaneous recordings from multiple neurons may produce huge amounts of information. Traditional tools based on classical statistics are either insufficient to analyze multiple spike trains or sophisticated and expensive in computing terms. In this communication, we put to the test the idea that AI algorithms may be useful to gather information about the effective connectivity of neurons in local nuclei at a relatively low computing cost. To this end, we decided to explore the capacity of the algorithm C5.0 to retrieve information from a large series of spike trains obtained from a simulated neuronal circuit with a known structure. Combinatory, iterative and recursive processes using C5.0 were built to examine possibilities of increasing the performance of a direct application of the algorithm. Furthermore, we tested the applicability of these processes to a reduced dataset obtained from original biological recordings with unknown connectivity. This was obtained in house from a mouse in vitro preparation of the spinal cord. Results show that this algorithm can retrieve neurons monosynaptically connected to the target in simulated datasets within a single run. Iterative and recursive processes can identify monosynaptic neurons and disynaptic neurons under favorable conditions. Application of these processes to the biological dataset gives clues to identify neurons monosynaptically connected to the target. We conclude that the work presented provides substantial proof of concept for the potential use of AI algorithms to the study of effective connectivity.

PMID:33796015 | PMC:PMC8007904 | DOI:10.3389/fninf.2021.561012

Cancer Inform. 2021 Mar 19;20:11769351211002494. doi: 10.1177/11769351211002494. eCollection 2021.

ABSTRACT

MOTIVATION: Despite increasing understanding of the molecular characteristics of cancer, chemotherapy success rates remain low for many cancer types. Studies have attempted to identify patient and tumor characteristics that predict sensitivity or resistance to different types of conventional chemotherapies, yet a concise model that predicts chemosensitivity based on gene expression profiles across cancer types remains to be formulated. We attempted to generate pan-cancer models predictive of chemosensitivity and chemoresistance. Such models may increase the likelihood of identifying the type of chemotherapy most likely to be effective for a given patient based on the overall gene expression of their tumor.

RESULTS: Gene expression and drug sensitivity data from solid tumor cell lines were used to build predictive models for 11 individual chemotherapy drugs. Models were validated using datasets from solid tumors from patients. For all drug models, accuracy ranged from 0.81 to 0.93 when applied to all relevant cancer types in the testing dataset. When considering how well the models predicted chemosensitivity or chemoresistance within individual cancer types in the testing dataset, accuracy was as high as 0.98. Cell line-derived pan-cancer models were able to statistically significantly predict sensitivity in human tumors in some instances; for example, a pan-cancer model predicting sensitivity in patients with bladder cancer treated with cisplatin was able to significantly segregate sensitive and resistant patients based on recurrence-free survival times (P = .048) and in patients with pancreatic cancer treated with gemcitabine (P = .038). These models can predict chemosensitivity and chemoresistance across cancer types with clinically useful levels of accuracy.

PMID:33795931 | PMC:PMC7983245 | DOI:10.1177/11769351211002494

Nat Neurosci. 2021 Apr 1. doi: 10.1038/s41593-021-00827-3. Online ahead of print.

ABSTRACT

The neurodegenerative disease spinal muscular atrophy (SMA) is caused by deficiency in the survival motor neuron (SMN) protein. Currently approved SMA treatments aim to restore SMN, but the potential for SMN expression beyond physiological levels is a unique feature of adeno-associated virus serotype 9 (AAV9)-SMN gene therapy. Here, we show that long-term AAV9-mediated SMN overexpression in mouse models induces dose-dependent, late-onset motor dysfunction associated with loss of proprioceptive synapses and neurodegeneration. Mechanistically, aggregation of overexpressed SMN in the cytoplasm of motor circuit neurons sequesters components of small nuclear ribonucleoproteins, leading to splicing dysregulation and widespread transcriptome abnormalities with prominent signatures of neuroinflammation and the innate immune response. Thus, long-term SMN overexpression interferes with RNA regulation and triggers SMA-like pathogenic events through toxic gain-of-function mechanisms. These unanticipated, SMN-dependent and neuron-specific liabilities warrant caution on the long-term safety of treating individuals with SMA with AAV9-SMN and the risks of uncontrolled protein expression by gene therapy.

PMID:33795885 | DOI:10.1038/s41593-021-00827-3

Nat Struct Mol Biol. 2021 Apr 1. doi: 10.1038/s41594-021-00576-8. Online ahead of print.

ABSTRACT

Ubiquitin-specific protease 1 (USP1) acts together with the cofactor UAF1 during DNA repair processes to specifically remove monoubiquitin signals. One substrate of the USP1-UAF1 complex is the monoubiquitinated FANCI-FANCD2 heterodimer, which is involved in the repair of DNA interstrand crosslinks via the Fanconi anemia pathway. Here we determine structures of human USP1-UAF1 with and without ubiquitin and bound to monoubiquitinated FANCI-FANCD2. The crystal structures of USP1-UAF1 reveal plasticity in USP1 and key differences to USP12-UAF1 and USP46-UAF1, two related proteases. A cryo-EM reconstruction of USP1-UAF1 in complex with monoubiquitinated FANCI-FANCD2 highlights a highly orchestrated deubiquitination process, with USP1-UAF1 driving conformational changes in the substrate. An extensive interface between UAF1 and FANCI, confirmed by mutagenesis and biochemical assays, provides a molecular explanation for the requirement of both proteins, despite neither being directly involved in catalysis. Overall, our data provide molecular details of USP1-UAF1 regulation and substrate recognition.

PMID:33795880 | DOI:10.1038/s41594-021-00576-8

Nat Methods. 2021 Apr 1. doi: 10.1038/s41592-021-01105-7. Online ahead of print.

ABSTRACT

SNT is an end-to-end framework for neuronal morphometry and whole-brain connectomics that supports tracing, proof-editing, visualization, quantification and modeling of neuroanatomy. With an open architecture, a large user base, community-based documentation, support for complex imagery and several model organisms, SNT is a flexible resource for the broad neuroscience community. SNT is both a desktop application and multi-language scripting library, and it is available through the Fiji distribution of ImageJ.

PMID:33795878 | DOI:10.1038/s41592-021-01105-7

Sci Rep. 2021 Apr 1;11(1):7427. doi: 10.1038/s41598-021-86766-2.

ABSTRACT

The main aim of this study was to elucidate the effect of individual and joint fertilization with P and Zn on maize plants grown on typical Mediterranean soils with a limited Zn availability. For this purpose, we examined the effects of P and Zn fertilization individually and in combination on growth, yield and grain protein content in maize grown in pots filled with three different Mediterranean soils (LCV, FER and INM). Phosphorus and Zn translocation to grain was impaired, and aboveground dry matter and yield at harvest reduced by 8-85% (LCV and FER), in plants treated with Zn or P alone relative to unfertilized (control) plants. In contrast, joint fertilization with P and Zn enhanced translocation of these nutrients to grain and significantly increased aboveground dry matter (30% in LCV, 50% in FER and 250% in INM) and grain Zn availability in comparison with control plants. Also, joint application of both nutrients significantly increased grain P (LCV) and Zn (LCV and FER) use efficiency relative P and Zn, respectively, alone. Yield was increased between 31% in LCV and 121% in FER relative to control plants, albeit not significantly. Fertilization with P or Zn significantly influenced the abundance of specific proteins affecting grain quality (viz., storage, lys-rich and cell wall proteins), which were more abundant in mature grains from plants fertilized with Zn alone and, to a lesser extent, P + Zn. Sustainable strategies in agriculture should consider P-Zn interactions in maize grown on soils with a limited availability of Zn, where Zn fertilization is crucial to ensure grain quality.

PMID:33795774 | DOI:10.1038/s41598-021-86766-2

Sci Rep. 2021 Apr 1;11(1):7373. doi: 10.1038/s41598-021-86742-w.

ABSTRACT

Macrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

PMID:33795737 | DOI:10.1038/s41598-021-86742-w

Nat Commun. 2021 Apr 1;12(1):2144. doi: 10.1038/s41467-021-22614-1.

NO ABSTRACT

PMID:33795662 | DOI:10.1038/s41467-021-22614-1

Science. 2021 Apr 1:eaba8490. doi: 10.1126/science.aba8490. Online ahead of print.

ABSTRACT

Transcription factor IID (TFIID) recognizes core promoters and supports preinitiation complex (PIC) assembly for RNA polymerase (Pol) II-mediated eukaryotic transcription. Here, we determined the structures of human TFIID-based PIC in three stepwise assembly states and revealed two-track PIC assembly: stepwise promoter deposition to Pol II and extensive modular reorganization on track I (on TATA-DBE promoters) versus direct promoter deposition on track II (on TATA-only and TATA-less promoters). The two tracks converge at ~50-subunit holo-PIC in identical conformation, whereby TFIID stabilizes PIC organization and supports loading (CDK)-activating kinase (CAK) onto Pol II and CAK-mediated phosphorylation of Pol II C-terminal domain. Unexpectedly, TBP of TFIID similarly bends TATA box and TATA-less promoters in PIC. Our study provides structural visualization of stepwise PIC assembly on highly diversified promoters.

PMID:33795473 | DOI:10.1126/science.aba8490

Science. 2021 Apr 2;372(6537):eaba1786. doi: 10.1126/science.aba1786.

ABSTRACT

T cell exhaustion limits immune responses against cancer and is a major cause of resistance to chimeric antigen receptor (CAR)-T cell therapeutics. Using murine xenograft models and an in vitro model wherein tonic CAR signaling induces hallmark features of exhaustion, we tested the effect of transient cessation of receptor signaling, or rest, on the development and maintenance of exhaustion. Induction of rest through enforced down-regulation of the CAR protein using a drug-regulatable system or treatment with the multikinase inhibitor dasatinib resulted in the acquisition of a memory-like phenotype, global transcriptional and epigenetic reprogramming, and restored antitumor functionality in exhausted CAR-T cells. This work demonstrates that rest can enhance CAR-T cell efficacy by preventing or reversing exhaustion, and it challenges the notion that exhaustion is an epigenetically fixed state.

PMID:33795428 | DOI:10.1126/science.aba1786

Plant Methods. 2021 Apr 1;17(1):36. doi: 10.1186/s13007-021-00736-3.

ABSTRACT

BACKGROUND: Peach diseases can cause severe yield reduction and decreased quality for peach production. Rapid and accurate detection and identification of peach diseases is of great importance. Deep learning has been applied to detect peach diseases using imaging data. However, peach disease image data is difficult to collect and samples are imbalance. The popular deep networks perform poor for this issue.

RESULTS: This paper proposed an improved Xception network named as L2MXception which ensembles regularization term of L2-norm and mean. With the peach disease image dataset collected, results on seven mainstream deep learning models were compared in details and an improved loss function was integrated with regularization term L2-norm and mean (L2M Loss). Experiments showed that the Xception model with L2M Loss outperformed the current best method for peach disease prediction. Compared to the original Xception model, the validation accuracy of L2MXception was up to 93.85%, increased by 28.48%.

CONCLUSIONS: The proposed L2MXception network may have great potential in early identification of peach diseases.

PMID:33794942 | DOI:10.1186/s13007-021-00736-3