Single-cell multi-gene identification of somatic mutations and gene rearrangements in cancer.

In this proof-of-concept study, we developed a single-cell method that provides genotypes of somatic alterations found in coding regions of messenger RNAs and integrates these transcript-based variants with their matching cell transcriptomes. We used nanopore adaptive sampling on single-cell complementary DNA libraries to validate coding variants in target gene transcripts, and short-read sequencing to characterize cell types harboring the mutations. CRISPR edits for 16 targets were identified using a cancer cell line, and known variants in the cell line were validated using a 352-gene panel. Variants in primary cancer samples were validated using target gene panels ranging from 161 to 529 genes. A gene rearrangement was also identified in one patient, with the rearrangement occurring in two distinct tumor sites.

Magnetic DNA random access memory with nanopore readouts and exponentially-scaled combinatorial addressing.

The storage of data in DNA typically involves encoding and synthesizing data into short oligonucleotides, followed by reading with a sequencing instrument. Major challenges include the molecular consumption of synthesized DNA, basecalling errors, and limitations with scaling up read operations for individual data elements. Addressing these challenges, we describe a DNA storage system called MDRAM (Magnetic DNA-based Random Access Memory) that enables repetitive and efficient readouts of targeted files with nanopore-based sequencing. By conjugating synthesized DNA to magnetic agarose beads, we enabled repeated data readouts while preserving the original DNA analyte and maintaining data readout quality. MDRAM utilizes an efficient convolutional coding scheme that leverages soft information in raw nanopore sequencing signals to achieve information reading costs comparable to Illumina sequencing despite higher error rates. Finally, we demonstrate a proof-of-concept DNA-based proto-filesystem that enables an exponentially-scalable data address space using only small numbers of targeting primers for assembly and readout.

Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.

INTRODUCTION: The classification of prostate cancer (PCa) lesions using Prostate Imaging Reporting and Data System (PI-RADS) suffers from poor inter-reader agreement. This study compared quantitative parameters or radiomic features from multiparametric magnetic resonance imaging (mpMRI) or positron emission tomography (PET), as inputs into machine learning (ML) to predict the Gleason scores (GS) of detected lesions for improved PCa lesion classification. METHODS: 20 biopsy-confirmed PCa subjects underwent imaging before radical prostatectomy. A pathologist assigned GS from tumour tissue. Two radiologists and one nuclear medicine physician delineated the lesions on the mpMR and PET images, yielding 45 lesion inputs. Seven quantitative parameters were extracted from the lesions, namely T2-weighted (T2w) image intensity, apparent diffusion coefficient (ADC), transfer constant (KTRANS), efflux rate constant (Kep), and extracellular volume ratio (Ve) from mpMR images, and SUVmean and SUVmax from PET images. Eight radiomic features were selected out of 109 radiomic features from T2w, ADC and PET images. Quantitative parameters or radiomic features, with risk factors of age, prostate-specific antigen (PSA), PSA density and volume, of 45 different lesion inputs were input in different combinations into four ML models - Decision Tree (DT), Support Vector Machine (SVM), k-Nearest-Neighbour (kNN), Ensembles model (EM). RESULTS: SUVmax yielded the highest accuracy in discriminating detected lesions. Among the 4 ML models, kNN yielded the highest accuracies of 0.929 using either quantitative parameters or radiomic features with risk factors as input. CONCLUSIONS: ML models' performance is dependent on the input combinations and risk factors further improve ML classification accuracy.

Recent nanobiotechnological advancements in lignocellulosic biomass valorization: A review.

Increase in human population, rapid industrialization, excessive utilization of fossil fuel utilization and anthropogenic activities have caused serious threats to the environment in terms of greenhouse gas emissions (GHGs), global warming, air pollution, acid rain, etc. This destruction in sustainability can be averted by a paradigm shift in the fuel production from fossil resources to bioenergy. Amongst different forms of bioenergy, lignocellulosic biomass can be utilized as an attractive substrate for the production of several high-value products owing to its renewability, easy availability, and abundance. Additionally, utilization of these waste biomasses reduces the environmental hazards associated with its disposal. Impedance of lignin and crystalline nature of cellulose pose major bottlenecks in biomass based energy. Though, several physio-chemicals processes are recommended as mitigation route but none of them seems to be promising for large scale application. In recent years, a right fusion of biological treatment combined with nanotechnology for efficient pretreatment and subsequent hydrolysis of biomass by ubiquitous enzymes seems to be promising alternative. In addition, to overcome these difficulties, nanotechnology-based methods have been recently adopted in catalytic valorization of lignocellulosic biomass. The present review has critically discussed the application of nano-biotechnology in lignocellulosic biomass valorization in terms of pretreatment and hydrolysis. A detailed discussion on the application of various nanoparticles in these processes, enzyme immobilization and end-production utilization is presented in this review. Finally, the review emphasizes the major challenges of this process along with different routes and recommendations to address the issues.

COVID-19 transmission, vulnerability, persistence and nanotherapy: a review.

End 2019, the zoonotic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), named COVID-19 for coronavirus disease 2019, is the third adaptation of a contagious virus following the severe acute respiratory syndrome coronavirus in 2002, SARS-CoV, and the Middle East respiratory syndrome virus in 2012, MERS-CoV. COVID-19 is highly infectious and virulent compared to previous outbreaks. We review sources, contagious routes, preventive measures, pandemic, outbreak, epidemiology of SARS-CoV, MERS-CoV and SARS-CoV-2 from 2002 to 2020 using a Medline search. We discuss the chronology of the three coronaviruses, the vulnerability of healthcare workers, coronaviruses on surface and in wastewater, diagnostics and cures, and measures to prevent spreading.

Immunotherapeutics for Covid-19 and post vaccination surveillance.

Severe acute respiratory syndrome coronavirus (SARS-CoV-2) has emerged as a pandemic and named as novel coronavirus disease (nCOVID-19). SARS-CoV-2 is different from other known viruses due to multiple mutations on the sites of nonstructural proteins (NSP) 2 and 3, and the varying nature of virulence between different persons. Immunotherapies such as vaccines and monoclonal antibodies have a protective effect on the patients bringing them to the front of the line of potential treatments. The present review intends to cover the development of 20 different vaccine candidates categorized under live attenuated vaccines, inactivated vaccines, subunit vaccines, viral vector-based vaccines, and nucleic acid vaccines. Formulation of these vaccine candidates by various companies in collaboration with global organizations and their status of clinical trials were addressed. On the other hand, various approaches for post-vaccination surveillance using nucleic acid and protein biomarkers imbued on suitable platforms were also highlighted to sum up the immune therapeutics for Covid-19.

CLT030, a leukemic stem cell-targeting CLL1 antibody-drug conjugate for treatment of acute myeloid leukemia.

The current standard of care for acute myeloid leukemia (AML) is largely ineffective with very high relapse rates and low survival rates, mostly due to the inability to eliminate a rare population of leukemic stem cells (LSCs) that initiate tumor growth and are resistant to standard chemotherapy. RNA-sequencing analysis on isolated LSCs confirmed C-type lectin domain family 12 member A (CLL1, also known as CLEC12A) to be highly expressed on LSCs but not on normal hematopoietic stem cells (HSCs) or other healthy organ tissues. Expression of CLL1 was consistent across different types of AML. We developed CLT030 (CLL1-ADC), an antibody-drug conjugate (ADC) based on a humanized anti-CLL1 antibody with 2 engineered cysteine residues linked covalently via a cleavable linker to a highly potent DNA-binding payload, thus resulting in a site-specific and homogenous ADC product. The ADC is designed to be stable in the bloodstream and to release its DNA-binding payload only after the ADC binds to CLL1-expressing tumor cells, is internalized, and the linker is cleaved in the lysosomal compartment. CLL1-ADC inhibits in vitro LSC colony formation and demonstrates robust in vivo efficacy in AML cell tumor models and tumor growth inhibition in the AML patient-derived xenograft model. CLL1-ADC demonstrated a reduced effect on differentiation of healthy normal human CD34+ cells to various lineages as observed in an in vitro colony formation assay and in an in vivo xenotransplantation model as compared with CD33-ADC. These results demonstrate that CLL1-ADC could be an effective ADC therapeutic for the treatment of AML.

Meat species identification using DNA-luminol interaction and their slow diffusion onto the biochip surface.

Recently, there has been a growing concern of consumers on the authenticity of food ingredients including adulteration with porcine and/or its derivatives. Therefore, this work reports on the development of a novel, simple, sensitive and rapid luminol-based electrochemiluminescence (ECL) technique for Sus scrofa (Porcine) DNA detection. Porcine DNA was firstly amplified using loop-mediated isothermal amplification (LAMP) method and subsequently added to luminol solution for further ECL analysis for quantification. The DNA-luminol complexes were formed causing the diffusion of luminol towards the electrode surface to be slowed down and hindered that resulted in low luminol intensity. The LAMP-ECL sensor is shown to be highly specific, sensitive (≥0.1 pg/µL) and rapid (∼5 min for detection). Hence, by employing this principle with carbon screen-printed electrode (SPE), this technique has a potential to be developed further into a compact biosensor for the verifying food authenticity.

Colorimetric Nucleic Acid Detection on Paper Microchip Using Loop Mediated Isothermal Amplification and Crystal Violet Dye.

Nucleic acid detection is of paramount importance in monitoring of microbial pathogens in food safety and infectious disease diagnostic applications. To address these challenges, a rapid, cost-effective label-free technique for nucleic acid detection with minimal instrumentations is highly desired. Here, we present paper microchip to detect and quantify nucleic acid using colorimetric sensing modality. The extracted DNA from food samples of meat as well as microbial pathogens was amplified utilizing loop-mediated isothermal amplification (LAMP). LAMP amplicon was then detected and quantified on a paper microchip fabricated in a cellulose paper and a small wax chamber utilizing crystal violet dye. The affinity of crystal violet dye toward dsDNA and positive signal were identified by changing the color from colorless to purple. Using this method, detection of Sus scrofa (porcine) and Bacillus subtilis (bacteria) DNA was possible at concentrations as low as 1 pg/µL (3.43 × 10 -1 copies/µL) and 10 pg/µL (2.2 × 103 copies/µL), respectively. This strategy can be adapted for detection of other DNA samples, with potential for development of a new breed of simple and inexpensive paper microchip at the point-of-need.

Quantitative 18F-fluorocholine positron emission tomography for prostate cancer: correlation between kinetic parameters and Gleason scoring.

BACKGROUND: The use of radiolabeled choline as a positron emission tomography (PET) agent for imaging primary tumors in the prostate has been evaluated extensively over the past two decades. There are, however, conflicting reports of its sensitivity and the relationship between choline PET imaging and disease staging is not fully understood. Moreover, relatively few studies have investigated the correlation between tracer uptake and histological tumor grade. This work quantified 18F-fluorocholine in tumor and healthy prostate tissue using pharmacokinetic modeling and stratified uptake parameters by histology grade. Additionally, the effect of scan time on the estimation of the kinetic exchange rate constants was evaluated, and the tracer influx parameters from full compartmental analysis were compared to uptake values quantified by Patlak and standardized uptake value (SUV) analyses. 18F-fluorocholine was administered as a 222 MBq bolus injection to ten patients with biopsy-confirmed prostate tumors, and dynamic PET data were acquired for 60 min. Image-derived arterial input functions were scaled by discrete blood samples, and a 2-tissue, 4-parameter model accounting for blood volume (2T4k+Vb) was used to perform fully quantitative compartmental modeling on tumor, healthy prostate, and muscle tissue. Subsequently, all patients underwent radical prostatectomy, and histological analyses were performed on the prostate specimens; kinetic parameters for tumors were stratified by Gleason score. Correlations were investigated between compartmental K 1 and K i parameters and SUV and Patlak slope; the effect of scan time on parameter bias was also evaluated. RESULTS: Choline activity curves in seven tumors, eight healthy prostate regions, and nine muscle regions were analyzed. Net tracer influx was generally higher in tumor relative to healthy prostate, with the values in the highest grade tumors markedly higher than those in lower grade tumors. Influx terms from Patlak and full compartmental modeling showed good correlation within individual tissue groups. Kinetic parameters calculated from the entire 60-min scan data were accurately reproduced from the first 30 min of acquired data (R 2 ≈ 0.9). CONCLUSIONS: Strong correlations were observed between K i and Patlak slope in tumor tissue, and K 1 and SUV were also correlated but to a lesser degree. Reliable estimates of all kinetic parameters can be achieved from the first 30 min of dynamic 18F-choline data. Although SUV, K 1, K i, and Patlak slope were found to be poor differentiators of low-grade tumor compared to healthy prostate tissue, they are strong indicators of aggressive disease.

A novel, sensitive and label-free loop-mediated isothermal amplification detection method for nucleic acids using luminophore dyes.

Electrochemiluminescence (ECL) has been widely rendered for nucleic acid testing. Here, we integrate loop-mediated isothermal amplification (LAMP) with ECL technique for DNA detection and quantification. The target LAMP DNA bound electrostatically with [Ru(bpy)3](+2) on the carbon electrode surface, and an ECL reaction was triggered by tripropylamine (TPrA) to yield luminescence. We illustrated this method as a new and highly sensitive strategy for the detection of sequence-specific DNA from different meat species at picogram levels. The proposed strategy renders the signal amplification capacities of TPrA and combines LAMP with inherently high sensitivity of the ECL technique, to facilitate the detection of low quantities of DNA. By leveraging this technique, target DNA of Sus scrofa (pork) meat was detected as low as 1pg/µL (3.43×10(-1)copies/µL). In addition, the proposed technique was applied for detection of Bacillus subtilis DNA samples and detection limit of 10pg/µL (2.2×10(3)copies/µL) was achieved. The advantages of being isothermal, sensitive and robust with ability for multiplex detection of bio-analytes makes this method a facile and appealing sensing modality in hand-held devices to be used at the point-of-care (POC).

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Visual Interpretation with Three-Dimensional Annotations (VITA): three-dimensional image interpretation tool for radiological reporting.

This paper introduces a software framework called Visual Interpretation with Three-Dimensional Annotations (VITA) that is able to automatically generate three-dimensional (3D) visual summaries based on radiological annotations made during routine exam reporting. VITA summaries are in the form of rotating 3D volumes where radiological annotations are highlighted to place important clinical observations into a 3D context. The rendered volume is produced as a Digital Imaging and Communications in Medicine (DICOM) object and is automatically added to the study for archival in Picture Archiving and Communication System (PACS). In addition, a video summary (e.g., MPEG4) can be generated for sharing with patients and for situations where DICOM viewers are not readily available to referring physicians. The current version of VITA is compatible with ClearCanvas; however, VITA can work with any PACS workstation that has a structured annotation implementation (e.g., Extendible Markup Language, Health Level 7, Annotation and Image Markup) and is able to seamlessly integrate into the existing reporting workflow. In a survey with referring physicians, the vast majority strongly agreed that 3D visual summaries improve the communication of the radiologists' reports and aid communication with patients.

Phenotype detection in morphological mutant mice using deformation features.

Large-scale global efforts are underway to knockout each of the approximately 25,000 mouse genes and interpret their roles in shaping the mammalian embryo. Given the tremendous amount of data generated by imaging mutated prenatal mice, high-throughput image analysis systems are inevitable to characterize mammalian development and diseases. Current state-of-the-art computational systems offer only differential volumetric analysis of pre-defined anatomical structures between various gene-knockout mice strains. For subtle anatomical phenotypes, embryo phenotyping still relies on the laborious histological techniques that are clearly unsuitable in such big data environment. This paper presents a system that automatically detects known phenotypes and assists in discovering novel phenotypes in muCT images of mutant mice. Deformation features obtained from non-linear registration of mutant embryo to a normal consensus average image are extracted and analyzed to compute phenotypic and candidate phenotypic areas. The presented system is evaluated using C57BL/10 embryo images. All cases of ventricular septum defect and polydactyly, well-known to be present in this strain, are successfully detected. The system predicts potential phenotypic areas in the liver that are under active histological evaluation for possible phenotype of this mouse line.

Hph1p and Hph2p, novel components of calcineurin-mediated stress responses in Saccharomyces cerevisiae.

Calcineurin is a Ca2+- and calmodulin-dependent protein phosphatase that plays a key role in animal and yeast physiology. In the yeast Saccharomyces cerevisiae, calcineurin is required for survival during several environmental stresses, including high concentrations of Na+, Li+, and Mn2+ ions and alkaline pH. One role of calcineurin under these conditions is to activate gene expression through its regulation of the Crz1p transcription factor. We have identified Hph1p as a novel substrate of calcineurin. HPH1 (YOR324C) and its homolog HPH2 (YAL028W) encode tail-anchored integral membrane proteins that interact with each other in the yeast two-hybrid assay and colocalize to the endoplasmic reticulum. Hph1p and Hph2p serve redundant roles in promoting growth under conditions of high salinity, alkaline pH, and cell wall stress. Calcineurin modifies the distribution of Hph1p within the endoplasmic reticulum and is required for full Hph1p activity in vivo. Furthermore, calcineurin directly dephosphorylates Hph1p and interacts with it through a sequence motif in Hph1p, PVIAVN. This motif is related to calcineurin docking sites in other substrates, such as NFAT and Crz1p, and is required for regulation of Hph1p by calcineurin. In contrast, Hph2p neither interacts with nor is dephosphorylated by calcineurin. Ca2+-induced Crz1p-mediated transcription is unaffected in hph1delta hph2delta mutants, and genetic analyses indicate that HPH1/HPH2 and CRZ1 act in distinct pathways downstream of calcineurin. Thus, Hph1p and Hph2p are components of a novel Ca2+- and calcineurin-regulated response required to promote growth under conditions of high Na+, alkaline pH, and cell wall stress.

Analysis of protein sequence/structure similarity relationships.

Current analyses of protein sequence/structure relationships have focused on expected similarity relationships for structurally similar proteins. To survey and explore the basis of these relationships, we present a general sequence/structure map that covers all combinations of similarity/dissimilarity relationships and provide novel energetic analyses of these relationships. To aid our analysis, we divide protein relationships into four categories: expected/unexpected similarity (S and S(?)) and expected/unexpected dissimilarity (D and D(?)) relationships. In the expected similarity region S, we show that trends in the sequence/structure relation can be derived based on the requirement of protein stability and the energetics of sequence and structural changes. Specifically, we derive a formula relating sequence and structural deviations to a parameter characterizing protein stiffness; the formula fits the data reasonably well. We suggest that the absence of data in region S(?) (high structural but low sequence similarity) is due to unfavorable energetics. In contrast to region S, region D(?) (high sequence but low structural similarity) is well-represented by proteins that can accommodate large structural changes. Our analyses indicate that there are several categories of similarity relationships and that protein energetics provide a basis for understanding these relationships.