De novo generation of a bright blue fluorophore from 2-oxoglutarate in biological samples

DTPP, a bright fluorophore with 2-pyridone and γ-lactam, is generated in a de novo manner from non-fluorogenic 2-oxoglutarate and specific amines. The DTPP-based fluorometry is applied to the analysis of 2-oxoglutarate in a biological sample.

Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects

Background Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. Results To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. Conclusions The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.

The Application of Metabolomics in Forensic Science with Focus on Forensic Toxicology and Time-of-Death Estimation

Recently, the diagnostic methods used by scientists in forensic examinations have enormously expanded. Metabolomics provides an important contribution to analytical method development. The main purpose of this review was to investigate and summarize the most recent applications of metabolomics in forensic science. The primary research method was an extensive review of available international literature in PubMed. The keywords “forensic” and “metabolomics” were used as search criteria for the PubMed database scan. Most authors emphasized the analysis of different biological sample types using chromatography methods. The presented review is a summary of recently published implementations of metabolomics in forensic science and types of biological material used and techniques applied. Possible opportunities for valuable metabolomics’ applications are discussed to emphasize the essential necessities resulting in numerous nontargeted metabolomics’ assays.

Multiplex genomic recording of enhancer and signal transduction activities in mammalian cells

Measurements of gene expression and signal transduction activity are conventionally performed with methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm, termed ENGRAM (ENhancer-driven Genomic Recording of transcriptional Activity in Multiplex), in which the activity and dynamics of multiple transcriptional reporters are stably recorded to DNA. ENGRAM is based on the prime editing-mediated insertion of signal- or enhancer-specific barcodes to a genomically encoded recording unit. We show how this strategy can be used to concurrently record the relative activity of at least hundreds of enhancers with high fidelity, sensitivity and reproducibility. Leveraging synthetic enhancers that are responsive to specific signal transduction pathways, we further demonstrate time- and concentration-dependent genomic recording of Wnt, NF-κB, and Tet-On activity. Finally, by coupling ENGRAM to sequential genome editing, we show how serially occurring molecular events can potentially be ordered. Looking forward, we envision that multiplex, ENGRAM-based recording of the strength, duration and order of enhancer and signal transduction activities has broad potential for application in functional genomics, developmental biology and neuroscience.

Evaluation of Sample Preparation Strategies for Human Milk and Plasma Proteomics

Sample preparation is the most critical step in proteomics as it directly affects the subset of proteins and peptides that can be reliably identified and quantified. Although a variety of efficient and reproducible sample preparation strategies have been developed, their applicability and efficacy depends much on the biological sample. Here, three approaches were evaluated for the human milk and plasma proteomes. Protein extracts were digested either in an ultrafiltration unit (filter-aided sample preparation, FASP) or in-solution (ISD). ISD samples were desalted by solid-phase extraction prior to nRPC-ESI-MS/MS. Additionally, milk and plasma samples were directly digested by FASP without prior protein precipitation. Each strategy provided inherent advantages and disadvantages for milk and plasma. FASP appeared to be the most time efficient procedure with a low miscleavage rate when used for a biological sample aliquot, but quantitation was less reproducible. A prior protein precipitation step improved the quantitation by FASP due to significantly higher peak areas for plasma and a much better reproducibility for milk. Moreover, the miscleavage rate for milk, the identification rate for plasma, and the carbamidomethylation efficiency were improved. In contrast, ISD of both milk and plasma resulted in higher miscleavage rates and is therefore less suitable for targeted proteomics.

Restricted Access Molecularly Imprinted Polymers for Biological Sample Preparation

Restricted access molecularly imprinted polymers (RAMIPs) have been efficiently used for the extraction of small organic molecules from untreated biological matrices (e.g. blood, plasma, serum, and milk). These materials have been obtained by modifying the external surface of conventional molecularly imprinted polymers (MIPs) with hydrophilic monomer grafting, crosslinked protein capsule or a combination of both. These sorbents aggregate the selectivity of MIPs with the ability to exclude macromolecules of restricted access materials (RAMs), being widely employed in solid phase extraction techniques, beyond their use in sensors. In this review, we discuss about the design and application of RAMIPs in biological sample preparation, emphasizing the future trends and remaining challenges of this technology for bioanalyses.

Multiplex genomic recording of enhancer and signal transduction activity in mammalian cells

Measurements of gene expression and signal transduction activity are conventionally performed with methods that require either the destruction or live imaging of a biological sample within the timeframe of interest. Here we demonstrate an alternative paradigm, termed ENGRAM (ENhancer-driven Genomic Recording of transcriptional Activity in Multiplex), in which the activity and dynamics of multiple transcriptional reporters are stably recorded to DNA. ENGRAM is based on the prime editing-mediated insertion of signal- or enhancer-specific barcodes to a genomically encoded recording unit. We show how this strategy can be used to concurrently genomically record the relative activity of at least hundreds of enhancers with high fidelity, sensitivity and reproducibility. Leveraging synthetic enhancers that are responsive to specific signal transduction pathways, we further demonstrate time- and concentration-dependent genomic recording of Wnt, NF-κB, and Tet-On activity. Finally, by coupling ENGRAM to sequential genome editing, we show how serially occurring molecular events can potentially be ordered. Looking forward, we envision that multiplex, ENGRAM-based recording of the strength, duration and order of enhancer and signal transduction activities has broad potential for application in functional genomics, developmental biology and neuroscience.

Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction

Here we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (~ 1 keV), applying it for the first time to map the distribution of stain in a fixed biological sample through its characteristic K-edge. Conventionally, because the photons detected at each pixel are distributed across as many as 200 energy channels, energy-selective images are characterised by low count-rates and poor signal-to-noise ratio. This means high X-ray exposures, long scan times and high doses are required to image unique spectral markers. Here, we achieve high quality energy-dispersive tomograms from low dose, noisy datasets using a dedicated iterative reconstruction algorithm. This exploits the spatial smoothness and inter-channel structural correlation in the spectral domain using two carefully chosen regularisation terms. For a multi-phase phantom, a reduction in scan time of 36 times is demonstrated. Spectral analysis methods including K-edge subtraction and absorption step-size fitting are evaluated for an ex vivo, single (iodine)-stained biological sample, where low chemical concentration and inhomogeneous distribution can affect soft tissue segmentation and visualisation. The reconstruction algorithms are available through the open-source Core Imaging Library. Taken together, these tools offer new capabilities for visualisation and elemental mapping, with promising applications for multiply-stained biological specimens.

Salivary Biomarkers in Lung Cancer

A very low percentage of lung cancer (LC) cases are discovered at an early and treatable stage of the disease, leading to an abysmally low 5-year survival rate. This underscores the immediate necessity for improved diagnostic, prognostic, and predictive biomarkers for LC. Biopsied lung tissue, blood, and plasma are common sources used for LC diagnosis and monitoring of the disease. A growing number of studies have reported saliva to be a useful biological sample for early and noninvasive detection of oral and systemic diseases. Nevertheless, salivary biomarker discovery remains underresearched. Here, we have compiled the available literature to provide an overview of the current understanding of salivary markers for LC detection and provided perspectives for future clinical significance. Valuable markers with diagnostic and prognostic potentials in LC have been discovered in saliva, including metabolic (catalase activity, triene conjugates, and Schiff bases), inflammatory (interleukin 10, C-X-C motif chemokine ligand 10), proteomic (haptoglobin, zinc-α-2-glycoprotein, and calprotectin), genomic (epidermal growth factor receptor), and microbial candidates (Veillonella and Streptococcus). In combination, with each other and with other established screening methods, these salivary markers could be useful for improving early detection of the disease and ultimately improve the survival odds of LC patients. The existing literature suggests that saliva is a promising biological sample for identification and validation of biomarkers in LC, but how saliva can be utilized most effectively in a clinical setting for LC management is still under investigation.