Core Sequence Research Articles

Axial T1-weighted imaging of the lumbar spine: a redundancy or an asset?

To determine the diagnostic value of axial T1-weighted imaging for patients suffering from lower back pain. In this retrospective study, 100 consecutive lumbar spine MRIs obtained in patients with chronic low back pain were reviewed in two sessions: First, readers viewed core sequences (sagittal T1-weighted, STIR and T2-weighted, and axial T2-weighted) with axial T1-weighted sequences, and second, readers viewed cores sequences alone. Readers recorded the presence of disc degeneration, nerve root compromise, facet joint arthritis, and stenosis at each lumbar spine level as well as the presence of lipoma of filum terminale (LFT), spondylolisthesis, transitional vertebrae, and fractures. The McNemar, Wilcoxon signed-rank, and student T tests were utilized. For 100 studies, 5 spine levels were evaluated (L1-L2 through L5-S1). There were cases of disc disease (444/500 bulges, 56/500 herniations), nerve root compromise (1/500 nerve enlargement, 36/500 contact only, 20/500 displacement or compression), facet arthritis (438/500), stenosis (58/500 central canal, 64/500 lateral recess, 137/500 neuroforaminal), 6/100 LFTs, and other abnormalities (58/500 spondylolisthesis, 10/100 transitional vertebrae, 10/500 fracture/spondylolysis). There was no difference in diagnostic performance between the interpretation sessions (with and without axial T1-weighted imaging) at any level (p > 0.05), although four small additional LFTs were identified with axial T1-weighted imaging availability. There was no clinically significant difference in the interpretation of lumbar spine MRI viewed with and without axial T1-weighted imaging, suggesting that the axial T1-weighted sequence does not add diagnostic value to routine lumbar spine MRI.

Smoking History and Higher Pack Years Predict Brain Atrophy in 9646 Healthy Individuals

AbstractBackgroundSmoking is a risk factor for both Alzheimer and vascular dementia. Understanding this risk requires an investigation of how smoking influences brain volume loss on MRI, a biomarker for neurodegeneration.MethodIn total, 9646 healthy participants from 4 sites were scanned on 1.5T MR with a whole‐body MR imaging protocol. Core whole body sequences included whole body coronal T1, STIR from vertex to feet, whole‐body axial DWI from vertex to proximal‐thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning volumetric software, FastSurfer, trained on over 134 participants age 27‐66, segmented 96 brain volumes. Smokers versus non‐smokers were compared by gray and white matter volumes normalized to total intracranial volume using a two tailed t‐test. Partial correlation analysis was done between pack years and brain volumes, controlling for age, sex, and total intracranial volume (TIV). The Benjamini Hochberg False Discovery Rate of 5% accounted for multiple comparisons.ResultOverall, the sample had an average age of 52.9±13.1 years with 3123 individuals (32.3%) self‐reporting a history of smoking with 3.72±10.08 pack years. The remaining 6523 persons (67.7%) were non‐smokers. Participants who smoked were older than non‐smokers (p = 0.024) and 51.55% were men versus 52.8% in the non‐smoker group (p = .218). Individuals with a history of smoking had lower normalized gray and white matter volumes compared to non‐smokers (t = 8.95, p = 4.39e‐19). Adjusting for age, sex, and TIV co‐variates and multiple comparisons, higher pack years of smoking predicted brain volume loss in: total gray matter volume (Partial R = ‐0.06, p = 2.19e‐8), total white matter volume (Partial R = ‐0.06, p = 4.26e‐9), hippocampus (Partial R = ‐0.05, p = 6.26e‐6), frontal cortex (Partial R = ‐0.06, p = 1.34e‐10), temporal lobes (Partial R = ‐0.06, p = 3.24e‐8), parietal lobe (Partial R = ‐0.04, p = 0.0008), orbital frontal cortex (Partial R = ‐0.05, p = 2.19e‐8), posterior cingulate gyrus (Partial R = ‐0.05, p = 2.97e‐7).ConclusionBoth smoking history and pack years are related to lower whole brain and regional volumes.

Deep Learning Derived Visceral Abdominal Fat Predicts Brain Atrophy at Midlife in 10,001 Individuals

AbstractBackgroundVisceral abdominal fat can predict health outcomes with increasing interest in applications on brain health.MethodA total of 10,001 healthy participants from four sites were scanned on 1.5T MR machines with a short whole‐body MR imaging protocol. Core whole body sequences included coronal T1, STIR from vertex to feet, whole‐body axial DWI from vertex to proximal‐thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning with FastSurfer trained on 134 participants aged 27‐66 and segmented 96 brain regions. A separate deep learning model was trained to segment abdominal visceral fat from the whole‐body coronal T1. Partial correlation analysis of visceral abdominal fat volume and brain volumes were evaluated, controlling for age, sex, and total intracranial volume. Benjamini‐Hochberg False Discovery Rate of 5% controlled for multiple comparisons. Logistic regression models determined risk of brain total gray and white matter atrophy based upon the highest quartile of visceral fat and lowest quartile of these brain volumes.ResultThis cohort had an average age of 52.97 ± 13.04 years with a range of 11‐97 years with 52.8% men and 47.2% women. Mean visceral abdominal fat was 3417.81 ± 514.88 ml for overweight persons (BMI ³ 25) and 5355.24 ± 505.04 for obese persons (BMI ³ 30). Even accounting for co‐variates and multiple comparisons, deep learning segmented visceral abdominal fat predicted atrophy in multiple brain regions including: total gray matter volume (Partial R = ‐.09, p = 1.17e‐19), total white matter volume (Partial R = ‐.09, p = 2.25e‐21), hippocampus (Partial R = ‐.02, p = .005), frontal cortex (Partial R = ‐.09, p = 1.79e‐19), temporal lobes (Partial R = ‐.12, p = 2.6e‐30), parietal lobes (Partial R = ‐.04, p = .0004), occipital lobe (Partial R = ‐.03, p = .002), orbital frontal cortex (Partial R = ‐.09, p = 3.76e‐21). Visceral fat predicted increased risk for lower total gray matter (age 20‐39: OR = 5.9; age 40‐59, OR = 5.4; 60‐80, OR = 5.1) and white matter atrophy: (age 20‐39: OR = 3.78; age 40‐59, OR = 4.4; 60‐80, OR = 5.1).ConclusionDeep learning determined increased visceral abdominal fat volume predicts brain volume loss and may represent a novel modifiable factor in determining brain health.

Smoking History and Higher Pack Years Predict Brain Atrophy in 9646 Healthy Individuals

AbstractBackgroundSmoking is a risk factor for both Alzheimer and vascular dementia. Understanding this risk requires an investigation of how smoking influences brain volume loss on MRI, a biomarker for neurodegeneration.MethodIn total, 9646 healthy participants from 4 sites were scanned on 1.5T MR with a whole‐body MR imaging protocol. Core whole body sequences included whole body coronal T1, STIR from vertex to feet, whole‐body axial DWI from vertex to proximal‐thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning volumetric software, FastSurfer, trained on over 134 participants age 27‐66, segmented 96 brain volumes. Smokers versus non‐smokers were compared by gray and white matter volumes normalized to total intracranial volume using a two tailed t‐test. Partial correlation analysis was done between pack years and brain volumes, controlling for age, sex, and total intracranial volume (TIV). The Benjamini Hochberg False Discovery Rate of 5% accounted for multiple comparisons.ResultOverall, the sample had an average age of 52.9±13.1 years with 3123 individuals (32.3%) self‐reporting a history of smoking with 3.72±10.08 pack years. The remaining 6523 persons (67.7%) were non‐smokers. Participants who smoked were older than non‐smokers (p = 0.024) and 51.55% were men versus 52.8% in the non‐smoker group (p = .218). Individuals with a history of smoking had lower normalized gray and white matter volumes compared to non‐smokers (t = 8.95, p = 4.39e‐19). Adjusting for age, sex, and TIV co‐variates and multiple comparisons, higher pack years of smoking predicted brain volume loss in: total gray matter volume (Partial R = ‐0.06, p = 2.19e‐8), total white matter volume (Partial R = ‐0.06, p = 4.26e‐9), hippocampus (Partial R = ‐0.05, p = 6.26e‐6), frontal cortex (Partial R = ‐0.06, p = 1.34e‐10), temporal lobes (Partial R = ‐0.06, p = 3.24e‐8), parietal lobe (Partial R = ‐0.04, p = 0.0008), orbital frontal cortex (Partial R = ‐0.05, p = 2.19e‐8), posterior cingulate gyrus (Partial R = ‐0.05, p = 2.97e‐7).ConclusionBoth smoking history and pack years are related to lower whole brain and regional volumes.

Deep Learning Derived Visceral Abdominal Fat Predicts Brain Atrophy at Midlife in 10,001 Individuals

AbstractBackgroundVisceral abdominal fat can predict health outcomes with increasing interest in applications on brain health.MethodA total of 10,001 healthy participants from four sites were scanned on 1.5T MR machines with a short whole‐body MR imaging protocol. Core whole body sequences included coronal T1, STIR from vertex to feet, whole‐body axial DWI from vertex to proximal‐thighs and axial T2 TSE without fat suppression from skull base to pelvis. Brain sequences were T1 MPRAGE and 2D FLAIR. Deep learning with FastSurfer trained on 134 participants aged 27‐66 and segmented 96 brain regions. A separate deep learning model was trained to segment abdominal visceral fat from the whole‐body coronal T1. Partial correlation analysis of visceral abdominal fat volume and brain volumes were evaluated, controlling for age, sex, and total intracranial volume. Benjamini‐Hochberg False Discovery Rate of 5% controlled for multiple comparisons. Logistic regression models determined risk of brain total gray and white matter atrophy based upon the highest quartile of visceral fat and lowest quartile of these brain volumes.ResultThis cohort had an average age of 52.97 ± 13.04 years with a range of 11‐97 years with 52.8% men and 47.2% women. Mean visceral abdominal fat was 3417.81 ± 514.88 ml for overweight persons (BMI ³ 25) and 5355.24 ± 505.04 for obese persons (BMI ³ 30). Even accounting for co‐variates and multiple comparisons, deep learning segmented visceral abdominal fat predicted atrophy in multiple brain regions including: total gray matter volume (Partial R = ‐.09, p = 1.17e‐19), total white matter volume (Partial R = ‐.09, p = 2.25e‐21), hippocampus (Partial R = ‐.02, p = .005), frontal cortex (Partial R = ‐.09, p = 1.79e‐19), temporal lobes (Partial R = ‐.12, p = 2.6e‐30), parietal lobes (Partial R = ‐.04, p = .0004), occipital lobe (Partial R = ‐.03, p = .002), orbital frontal cortex (Partial R = ‐.09, p = 3.76e‐21). Visceral fat predicted increased risk for lower total gray matter (age 20‐39: OR = 5.9; age 40‐59, OR = 5.4; 60‐80, OR = 5.1) and white matter atrophy: (age 20‐39: OR = 3.78; age 40‐59, OR = 4.4; 60‐80, OR = 5.1).ConclusionDeep learning determined increased visceral abdominal fat volume predicts brain volume loss and may represent a novel modifiable factor in determining brain health.

Ash1L ameliorates psoriasis via limiting neuronal activity-dependent release of miR-let-7b.

Psoriasis is a common autoimmune skin disease that significantly diminishes patients' quality of life. Interactions between primary afferents of the somatosensory system and the cutaneous immune system mediate the pathogenesis of psoriasis. This study aims to elucidate the molecular mechanisms of how primary sensory neurons regulate psoriasis formation. Skin and total RNA were extracted from wild-type (WT) and ASH1-like histone lysine methyltransferase (Ash1l+/- ) mice in both naive and imiquimod (IMQ)-induced psoriasis models. Immunohistochemistry, quantitative real-time polymerase chain reaction (qRT-PCR) and fluorescence-activated cell sorting (FACS) were then performed. Microfluidic chamber coculture was used to investigate the interaction between somatosensory neurons and bone marrow dendritic cells (BMDCs) ex vivo. Whole-cell patch clamp recordings were used to evaluate neuronal excitability after Ash1L haploinsufficiency in primary sensory neurons. The haploinsufficiency of ASH1L, a histone methyltransferase, in primary sensory neurons causes both neurite hyperinnervation and increased neuronal excitability, which promote miR-let-7b release from primary afferents in the skin in a neuronal activity-dependent manner. With a 'GUUGUGU' core sequence, miR-let-7b functions as an endogenous ligand of toll-like receptor 7 (TLR7) and stimulates the activation of dermal dendritic cells (DCs) and interleukin (IL)-23/IL-17 axis, ultimately exacerbating the symptoms of psoriasis. Thus, by limiting miR-let-7b release from primary afferents, ASH1L prevents dermal DC activation and ameliorates psoriasis. Somatosensory neuron ASH1L modulates the cutaneous immune system by limiting neuronal activity-dependent release of miR-let-7b, which can directly activate dermal DCs via TLR7 and ultimately lead to aggravated psoriatic lesion.

The intra-host evolutionary landscape and pathoadaptation of persistent Staphylococcus aureus in chronic rhinosinusitis.

Chronic rhinosinusitis (CRS) is a common chronic sinonasal mucosal inflammation associated with Staphylococcus aureus biofilm and relapsing infections. This study aimed to determine rates of S. aureus persistence and pathoadaptation in CRS patients by investigating the genomic relatedness and antibiotic resistance/tolerance in longitudinally collected S. aureus clinical isolates. A total of 68 S. aureus paired isolates (34 pairs) were sourced from 34 CRS patients at least 6 months apart. Isolates were grown into 48 h biofilms and tested for tolerance to antibiotics. A hybrid sequencing strategy was used to obtain high-quality reference-grade assemblies of all isolates. Single nucleotide variants (SNV) divergence in the core genome and sequence type clustering were used to analyse the relatedness of the isolate pairs. Single nucleotide and structural genome variations, plasmid similarity, and plasmid copy numbers between pairs were examined. Our analysis revealed that 41 % (14/34 pairs) of S. aureus isolates were persistent, while 59 % (20/34 pairs) were non-persistent. Persistent isolates showed episode-specific mutational changes over time with a bias towards events in genes involved in adhesion to the host and mobile genetic elements such as plasmids, prophages, and insertion sequences. Furthermore, a significant increase in the copy number of conserved plasmids of persistent strains was observed. This was accompanied by a significant increase in biofilm tolerance against all tested antibiotics, which was linked to a significant increase in biofilm biomass over time, indicating a potential biofilm pathoadaptive process in persistent isolates. In conclusion, our study provides important insights into the mutational changes during S. aureus persistence in CRS patients highlighting potential pathoadaptive mechanisms in S. aureus persistent isolates culminating in increased biofilm biomass.

MotifHub: Detection of trans-acting DNA motif group with probabilistic modeling algorithm

BackgroundTrans-acting factors are of special importance in transcription regulation, which is a group of proteins that can directly or indirectly recognize or bind to the 8–12 bp core sequence of cis-acting elements and regulate the transcription efficiency of target genes. The progressive development in high-throughput chromatin capture technology (e.g., Hi-C) enables the identification of chromatin-interacting sequence groups where trans-acting DNA motif groups can be discovered. The problem difficulty lies in the combinatorial nature of DNA sequence pattern matching and its underlying sequence pattern search space. MethodHere, we propose to develop MotifHub for trans-acting DNA motif group discovery on grouped sequences. Specifically, the main approach is to develop probabilistic modeling for accommodating the stochastic nature of DNA motif patterns. ResultsBased on the modeling, we develop global sampling techniques based on EM and Gibbs sampling to address the global optimization challenge for model fitting with latent variables. The results reflect that our proposed approaches demonstrate promising performance with linear time complexities. ConclusionMotifHub is a novel algorithm considering the identification of both DNA co-binding motif groups and trans-acting TFs. Our study paves the way for identifying hub TFs of stem cell development (OCT4 and SOX2) and determining potential therapeutic targets of prostate cancer (FOXA1 and MYC). To ensure scientific reproducibility and long-term impact, its matrix-algebra-optimized source code is released at http://bioinfo.cs.cityu.edu.hk/MotifHub.

Genome-wide identification of C2H2-ZFPs and functional analysis of BcZAT12 and BcZAT10 under cold stress in non-heading Chinese cabbage

Low temperature affects the quality and yield of non-heading Chinese cabbage.C2H2-type zinc finger proteins (C2H2-ZFPs) play an important role in various environmental stresses. To date, the functions of C2H2-ZFPs in non-heading Chinese cabbage are still uncharacterized. Here, 163 C2H2-ZFPs in non-heading Chinese cabbage were identified using the sequenced NHCC001 genome and classified into nine subfamilies. Then characterization of the C2H2-ZFPs was comprehensively investigated. Synteny analysis suggested that these genes these genes were highly conserved during evolution, which may be related to the triploid (WGT) event of NHCC001. Through a combination of genome-wide and transcriptome analysis, we identified two zinc finger protein factors BcZAT12 and BcZAT10 that are closely related to cold. Furthermore, it was found that both BcZAT12 and BcZAT10 were localized in the nucleus and highly expressed in leaves. VIGS and transient overexpression experiments indicated that BcZAT12 and BcZAT10 acted as transcriptional repressors to negatively regulate cold tolerance in non-heading Chinese cabbage during cold resistance. Surprisingly, we demonstrated that BcZAT12 can directly bind to the ACT core sequence of A (G/C) T-X3–4-A (G/C) T on the BcCBF1 promoter and inhibit its activity. Meanwhile, we discovered that BcNTL4 and BcNAC055 can bind to the G-BOX element on the promoter of BcZAT12 and negatively regulate the expression of BcZAT12. Interestingly, we found that BcABF2/4 can interact with BcZAT12, speculating that BcZAT12 may interact with BcABF2/4 to regulate the expression of cold-related genes. This study laid a foundation to further understand the functional role and regulatory mechanism of C2H2-ZFPs of non-heading Chinese cabbage under cold stress.

Spark-Based Label Diffusion and Label Selection Community Detection Algorithm for Metagenome Sequence Clustering

It is a challenge to assemble an enormous amount of metagenome data in metagenomics. Usually, metagenome cluster sequence before assembly accelerates the whole process. In SpaRC, sequences are defined as nodes and clustered by a parallel label propagation algorithm (LPA). To address the randomness of label selection from the parallel LPA during clustering and improve the completeness of metagenome sequence clustering, Spark-based parallel label diffusion and label selection community detection algorithm is proposed in the paper to obtain more accurate clustering results. In this paper, the importance of sequence is defined based on the Jaccard similarity coefficient and its degree. The core sequence is defined as the one with the largest importance in its located community. Three strategies are formulated to reduce the randomness of label selection. Firstly, the core sequence label diffuses over its located cluster and becomes the initial label of other sequences. Those sequences that do not receive an initial label will select the sequence label with the highest importance in the neighbor sequences. Secondly, we perform improved label propagation in order of label frequency and sequence importance to reduce the randomness of label selection. Finally, a merge small communities step is added to increase the completeness of clustered clusters. The experimental results show that our proposed algorithm can effectively reduce the randomness of label selection, improve the purity, completeness, and F-Measure and reduce the runtime of metagenome sequence clustering.

Genome-Wide Identification and Characterization of CLAVATA3/EMBRYO SURROUNDING REGION (CLE) Gene Family in Foxtail Millet (Setaria italica L.).

The CLAVATA3/EMBRYO-SURROUNDING REGION (CLE) genes encode signaling peptides that play important roles in various developmental and physiological processes. However, the systematic identification and characterization of CLE genes in foxtail millet (Setaria italica L.) remain limited. In this study, we identified and characterized 41 SiCLE genes in the foxtail millet genome. These genes were distributed across nine chromosomes and classified into four groups, with five pairs resulting from gene duplication events. SiCLE genes within the same phylogenetic group shared similar gene structure and motif patterns, while 34 genes were found to be single-exon genes. All SiCLE peptides harbored the conserved C-terminal CLE domain, with highly conserved positions in the CLE core sequences shared among foxtail millet, Arabidopsis, rice, and maize. The SiCLE genes contained various cis-elements, including five plant hormone-responsive elements. Notably, 34 SiCLE genes possessed more than three types of phytohormone-responsive elements on their promoters. Comparative analysis revealed higher collinearity between CLE genes in maize and foxtail millet, which may be because they are both C4 plants. Tissue-specific expression patterns were observed, with genes within the same group exhibiting similar and specific expression profiles. SiCLE32 and SiCLE41, classified in Group D, displayed relatively high expression levels in all tissues except panicles. Most SiCLE genes exhibited low expression levels in young panicles, while SiCLE6, SiCLE24, SiCLE25, and SiCLE34 showed higher expression in young panicles, with SiCLE24 down-regulated during later panicle development. Greater numbers of SiCLE genes exhibited higher expression in roots, with SiCLE7, SiCLE22, and SiCLE36 showing the highest levels and SiCLE36 significantly down-regulated after abscisic acid (ABA) treatment. Following treatments with ABA, 6-benzylaminopurine (6-BA), and gibberellic acid 3 (GA3), most SiCLE genes displayed down-regulation followed by subsequent recovery, while jasmonic acid (JA) and indole-3-acetic acid (IAA) treatments led to upregulation at 30 min in leaves. Moreover, identical hormone treatments elicited different expression patterns of the same genes in leaves and stems. This comprehensive study enhances our understanding of the SiCLE gene family and provides a foundation for further investigations into the functions and evolution of SiCLE genes in foxtail millet.

Core genome multilocus sequence typing of Clostridioides difficile to investigate transmission in the hospital setting

PurposeTraditional epidemiological investigations of healthcare-associated Clostridioides difficile infection (HA-CDI) are often insufficient. This study aimed to evaluate a procedure that includes secondary isolation and genomic typing of single toxigenic colonies using core genome multilocus sequence typing (cgMLST) for the investigation of C. difficile transmission.MethodsWe analyzed retrospectively all toxigenic C. difficile-positive stool samples stored at the Lausanne University Hospital over 6 consecutive months. All isolates were initially typed and classified using a modified double-locus sequence typing (DLST) method. Genome comparison of isolates with the same DLST and clustering were subsequently performed using cgMLST. The electronic administrative records of patients with CDI were investigated for spatiotemporal epidemiological links supporting hospital transmission. A comparative descriptive analysis between genomic and epidemiological data was then performed.ResultsFrom January to June 2021, 86 C. difficile isolates were recovered from thawed samples of 71 patients. Thirteen different DLST types were shared by > 1 patient, and 13 were observed in single patients. A genomic cluster was defined as a set of isolates from different patients with ≤ 3 locus differences, determined by cgMLST. Seven genomic clusters were identified, among which plausible epidemiological links were identified in only 4/7 clusters.ConclusionAmong clusters determined by cgMLST analysis, roughly 40% included unexplained HA-CDI acquisitions, which may be explained by unidentified epidemiological links, asymptomatic colonization, and/or shared common community reservoirs. The use of DLST, followed by whole genome sequencing analysis, is a promising and cost-effective stepwise approach for the investigation of CDI transmission in the hospital setting.

Reconstructing the Paleoenvironmental Evolution of Lake Kolon (Hungary) through Palaeoecological, Statistical and Historical Analyses

The research utilizes an interdisciplinary approach, combining geological, ecological, and historical methods. It delves into the environmental evolution of Lake Kolon over a span of 17,700 years, shedding light on the intricate interplay between geological processes and ecological changes. The historical, statistical (PCA, DCA), and palaeoecological analyses centers on a core sequence situated in the heart of the lake, building upon previous research endeavors (pollen, malacological, macrobotanical and sedimentological analyses with radiocarbon dating). Forest fires occurred at the end of the Last Glacial Maximum (LGM); the boreal forest–steppe environment changed into temperate deciduous forest at the Pleistocene–Holocene boundary; human-induced environmental change into open parkland occurred; and from medieval times, communities used the land as pasture. This type of reconstruction is crucial for understanding how ecosystems respond to climate change over time, which has broader implications for modern-day conservation efforts and managing ecosystems in the face of ongoing climate change.

KaScape: a sequencing-based method for global characterization of protein‒DNA binding affinity

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we developed the KaScape method, in which TFs bind to all possible DNA sequences in the same DNA pool where DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to a length such as 4, 5, 6, or 7. After separating bound from unbound double-stranded DNAs (dsDNAs), their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we developed three-dimensional KaScape viewing software based on a K-mer graph. We applied KaScape to 12 plant TF family AtWRKY proteins and found that all AtWRKY proteins bound to the core sequence GAC with similar profiles. KaScape can detect not only binding sequences consistent with the consensus W-box “TTGAC(C/T)” but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method for quantitatively characterizing the relative binding strength of a TF with all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate- and low-affinity binding sites.

Genomic evidence of genetic diversity and functional evolution in Flavobacterium columnare.

Flavobacterium columnare is the causative agent of columnaris disease in freshwater fish. Columnaris disease can cause heavy economic losses in aquaculture. In this study, whole-genome sequencing was used to characterize this pathogen. F. columnare isolate AH-01 had a circular chromosome and plasmid that encoded a total of 3,022 genes. Isolate GX-01 only had a circular chromosome and encoded 2,965 genes. Genomic islands, prophage regions, and CRISPR/Cas systems were identified in both genomes. Both genomes presented evidence of gene variation and horizontal transfer, both of which are the essential components of genetic diversity, genome plasticity, and functional evolution. Single-gene phylogeny and comparative genome analyses were performed to investigate the variation and evolution of this pathogen. Genetic analysis of 16S rRNA and housekeeping gene sequences significantly clustered 55 F. columnare isolates into four clades. The intragroup identity of the 16S rRNA gene exceeded 99%, while the intergroup identity was below the species delineation threshold. We discovered significant translocation, inversion, and rearrangement events that influenced local synteny within each group. Notably, the observed alignments varied considerably among all the studied groups. The core genomes of all strains with available sequences comprised 747 genes, corresponding to approximately 25% of the genome. Core genome multilocus sequence typing, genome-wide orthology and phylogenetic analyses, and average nucleotide identity suggested that the currently existing F. columnare was an assemblage of several distinct species, with levels of divergence at least equivalent to those between recognized bacterial species. The present investigation provided genomic evidence of gene variation and horizontal transfer, which were the basis of genetic diversity, genome plasticity, and functional evolution. The findings supported a proposed new taxonomic perspective on F. columnare.

Alanine Scanning of the Unstructured Region of Ara h 2 and of a Related Mimotope Reveals Critical Amino Acids for IgE Binding.

The unstructured region of Ara h 2, referred to as epitope 3, contains a repeated motif, DYPSh (h = hydroxyproline) that is important for IgE binding. IgE binding assays to 20mer and shorter peptides of epitope 3, defines a 16mer core sequence containing one copy of the DPYSh motif, DEDSYERDPYShSQDP. Thisstudy performs alanine scanning of this and a related 12mer mimotope, LLDPYAhRAWTK. IgE binding, using a pool of 10 sera and with individual sera, is greatly reduced when alanine is substituted for aspartate at position 8 (D8; p < 0.01), tyrosine at position 10 (Y10; p < 0.01), and hydroxyproline at position 12 (h12; p < 0.001). IgE binding to alanine-substituted peptides of a mimotope containing the DPY_h motif confirm the critical importance of Y (p < 0.01) and h (p < 0.01), but not D. Molecular modeling of the core and mimotope suggests an h-dependent conformational basis for the recognition of these sequences by polyclonal IgE. IgE from pooled sera and individual sera differentially bound amino acids throughout the sequences of Epitope 3 and its mimotope, with Y10 and h12 being most important for all sera. These results are highly significant for designing hypoallergenic forms of Ara h 2.

Contributions of the N-terminal flanking residues of an antigenic peptide from the Japanese cedar pollen allergen Cry j 1 to the T-cell activation by HLA-DP5.

Cry j 1 is a major allergen present in Japanese cedar (Cryptomeria japonica) pollens. Peptides with the core sequence of KVTVAFNQF from Cry j 1 ('pCj1') bind to HLA-DP5 and activate Th2 cells. In this study, we noticed that Ser and Lys at positions -2 and -3, respectively, in the N-terminal flanking (NF) region to pCj1 are conserved well in HLA-DP5-binding allergen peptides. A competitive binding assay showed that the double mutation of Ser(-2) and Lys(-3) to Glu [S(P-2)E/K(P-3)E] in a 13-residue Cry j 1 peptide (NF-pCj1) decreased its affinity for HLA-DP5 by about 2-fold. Similarly, this double mutation reduced, by about 2-fold, the amount of NF-pCj1 presented on the surface of mouse antigen-presenting dendritic cell line 1 (mDC1) cells stably expressing HLA-DP5. We established NF-pCj1-specific and HLA-DP5-restricted CD4+ T-cell clones from HLA-DP5 positive cedar pollinosis (CP) patients, and analyzed their IL-2 production due to the activation of mouse TG40 cells expressing the cloned T-cell receptor by the NF-pCj1-presenting mDC1 cells. The T-cell activation was actually decreased by the S(P-2)E/K(P-3)E mutation, corresponding to the reduction in the peptide presentation by this mutation. In contrast, the affinity of NF-pCj1·HLA-DP5 for the T-cell receptor was not affected by the S(P-2)E/K(P-3)E mutation, as analyzed by surface plasmon resonance. Considering the positional and side-chain differences of these NF residues from previously reported T-cell activating sequences, the mechanisms of enhanced T-cell activation by Ser(-2) and Lys(-3) of NF-pCj1 may be novel.

X-ray Crystallographic Study of Preferred Spacing by the NF-κB p50 Homodimer on κB DNA.

Though originally characterized as an inactive or transcriptionally repressive factor, the NF-κB p50 homodimer has become appreciated as a physiologically relevant driver of specific target gene expression. By virtue of its low affinity for cytoplasmic IκB protein inhibitors, p50 accumulates in the nucleus of resting cells, where it is a binding target for the transcriptional co-activator IκBζ. In this study, we employed X-ray crystallography to analyze the structure of the p50 homodimer on κB DNA from the promoters of human interleukin-6 (IL-6) and neutrophil-gelatinase-associated lipocalin (NGAL) genes, both of which respond to IκBζ. The NF-κB p50 homodimer binds 11-bp on IL-6 κB DNA, while, on NGAL κB DNA, the spacing is 12-bp. This begs the question: what DNA binding mode is preferred by NF-κB p50 homodimer? To address this, we engineered a "Test" κB-like DNA containing the core sequence 5'-GGGGAATTCCCC-3' and determined its X-ray crystal structure in complex with p50. This revealed that, when presented with multiple options, NF-κB p50 homodimer prefers to bind 11-bp, which necessarily imposes asymmetry on the complex despite the symmetry inherent in both the protein and its target DNA, and that the p50 dimerization domain can contact DNA via distinct modes.

Advances in Alzheimer's Disease-Associated Aβ Therapy Based on Peptide.

Alzheimer's disease (AD) urgently needs innovative treatments due to the increasing aging population and lack of effective drugs and therapies. The amyloid fibrosis of AD-associated β-amyloid (Aβ) that could induce a series of cascades, such as oxidative stress and inflammation, is a critical factor in the progression of AD. Recently, peptide-based therapies for AD are expected to be great potential strategies for the high specificity to the targets, low toxicity, fast blood clearance, rapid cell and tissue permeability, and superior biochemical characteristics. Specifically, various chiral amino acids or peptide-modified interfaces draw much attention as effective manners to inhibit Aβ fibrillation. On the other hand, peptide-based inhibitors could be obtained through affinity screening such as phage display or by rational design based on the core sequence of Aβ fibrosis or by computer aided drug design based on the structure of Aβ. These peptide-based therapies can inhibit Aβ fibrillation and reduce cytotoxicity induced by Aβ aggregation and some have been shown to relieve cognition in AD model mice and reduce Aβ plaques in mice brains. This review summarizes the design method and characteristics of peptide inhibitors and their effect on the amyloid fibrosis of Aβ. We further describe some analysis methods for evaluating the inhibitory effect and point out the challenges in these areas, and possible directions for the design of AD drugs based on peptides, which lay the foundation for the development of new effective drugs in the future.

Analysis of transmission-related third-generation cephalosporin-resistant Enterobacterales by electronic data mining and core genome multi-locus sequence typing

To contain intra-hospital transmission of third-generation cephalosporin-resistant Enterobacterales (3GCR-E), contact isolation precautions are recommended. To quantify transmissions of 3GCR Escherichia coli and 3GCR Klebsiella pneumoniae within a hospital. An automated outbreak detection system (AODS) was used to identify clusters (N≥2) of 3GCR Enterobacterales for the years 2016, 2018 and 2020. Clusters were defined by phenotypic agreement of microbiological results and spatial and temporal relationship. Core genome multi-locus sequence typing (cgMLST) was used to confirm whether the cluster isolates were transmitted between patients. A total of 4343 3GCR E.coli and 1377 K.pneumoniae isolates were analysed. Among the 3GCR E.coli isolates, the AODS identified 304 isolates as cluster isolates, the median cluster size was two (range: 2-5). The cgMLST analysis revealed that a total of 23 (7.5%) 3GCR E.coli cluster isolates were transmission-associated, of which 20 isolates (87%) were detected in intensive care patients. Among the 3GCR K.pneumoniae isolates, the AODS identified 73 isolates as cluster isolates, the median cluster size was two (range: 2-4). CgMLST revealed that 35 (48%) 3GCR K.pneumoniae cluster isolates were transmission associated, of which 27 isolates (77%) were detected in intensive care patients. For 3GCR K.pneumoniae, cgMLST confirmed the AODS results more frequently than for 3GCR E.coli. Therefore, contact isolation precautions for 3GCR K.pneumoniae may be appropriate on intensive care units, but only in certain circumstances, such as outbreaks, for Enterobacterales with lower transmissibility, such as E. coli.