Human Metabolic Enzymes Deficiency: A Genetic Mutation Based Approach

Recent advances on applications of single-walled carbon nanotubes as cutting-edge optical nanosensors for biosensing technologies

Single-walled carbon nanotubes (SWCNTs) possess outstanding photophysical properties which has garnered interest towards utilizing these materials for biosensing and imaging applications. The near-infrared (NIR) fluorescence within the tissue transparent region along with their photostability and sizes in the nanoscale make SWCNTs valued candidates for the development of optical sensors. In this review, we discuss recent advances in the development and the applications of SWCNT-based nano-biosensors. An overview of SWCNT's structural and photophysical properties, sensor development, and sensing mechanisms are described. Examples of SWCNT-based optical nanosensors for detection of disease biomarkers, pathogens (bacteria and viruses), plant stressors, and environmental contaminants including heavy metals and disinfectants are provided. Molecular detection in biofluids, in vitro, and in vivo (small animal models and plants) are highlighted, and sensor integration into portable substrates for implantable and wearable sensing devices has been discussed. Recent advancements, which include high throughput assays and the use of machine learning models to predict more sensitive and robust sensing outcomes are discussed. Current limitations and future perspectives on translation of SWCNT optical probes into clinical practices have been provided.

Determination of Normal Range of Acylcarnitine in Neonatal Dried Blood Spots using LC-MS/MS

Background

Acylcarnitine is one of the crucial markers of fatty acid metabolism, and examination of their level in infants can reveal several Inherited Metabolic Disorders (IDM) or Inborn errors of Metabolism (IEM). Because of the great importance of hereditary, metabolic, and other inherited disorders early diagnosis before the appearance of clinical symptoms, this study was carried out to establish a reference range for carnitine analytes and to identify acylcarnitine profiles in normal weight neonatal dried blood spots (DBS) specimens.

Methods

By using liquid chromatography tandem mass spectrometry (LC-MS/MS) for neonatal screening and eventually the examination and analysis of LC-MS/MS results, 34 acylcarnitine derivatives were identified.

Results

The normal range for acylcarnitine analytes with carbon numbers ranging from zero to 18, both main and the branched ones, were ultimately measured. Afterward, they were compared with the results of some other diagnostic laboratories to be verified.

Conclusions

This study differed from the other findings, which could be due to diversity in population and work methods. However, the reference range of most acylcarnitine derivatives in Tehran closely aligned with this study's findings.

Engineering of Therapeutic and Detoxifying Enzymes

Therapeutic enzymes present excellent opportunities for the treatment of human disease, modulation of metabolic pathways and system detoxification. However, current use of enzyme therapy in the clinic is limited as naturally occurring enzymes are seldom optimal for such applications and require substantial improvement by protein engineering. Engineering strategies such as design and directed evolution that have been successfully implemented for industrial biocatalysis can significantly advance the field of therapeutic enzymes, leading to biocatalysts with new-to-nature therapeutic activities, high selectivity, and suitability for medical applications. This minireview highlights case studies of how state-of-the-art and emerging methods in protein engineering are explored for the generation of therapeutic enzymes and discusses gaps and future opportunities in the field of enzyme therapy.

Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design

Emerging computational tools promise to revolutionize protein engineering for biocatalytic applications and accelerate the development timelines previously needed to optimize an enzyme to its more efficient variant. For over a decade, the benefits of predictive algorithms have helped scientists and engineers navigate the complexity of functional protein sequence space. More recently, spurred by dramatic advances in underlying computational tools, the promise of faster, cheaper, and more accurate enzyme identification, characterization, and engineering has catapulted terms such as artificial intelligence and machine learning to the must-have vocabulary in the field. This Perspective aims to showcase the current status of applications in pharmaceutical industry and also to discuss and celebrate the innovative approaches in protein science by highlighting their potential in selected recent developments and offering thoughts on future opportunities for biocatalysis. It also critically assesses the technology's limitations, unanswered questions, and unmet challenges.

Mapping human disease-associated enzymes into Reactome allows characterization of disease groups and their interactions

According to databases such as OMIM, Humsavar, Clinvar and Monarch, 1494 human enzymes are presently associated to 2539 genetic diseases, 75% of which are rare (with an Orphanet code). The Mondo ontology initiative allows a standardization of the disease name into specific codes, making it possible a computational association between genes, variants, diseases, and their effects on biological processes. Here, we tackle the problem of which biological processes enzymes can affect when the protein variant is disease-associated. We adopt Reactome to describe human biological processes, and by mapping disease-associated enzymes in the Reactome pathways, we establish a Reactome-disease association. This allows a novel categorization of human monogenic and polygenic diseases based on Reactome pathways and reactions. Our analysis aims at dissecting the complexity of the human genetic disease universe, highlighting all the possible links within diseases and Reactome pathways. The novel mapping helps understanding the biochemical/molecular biology of the disease and allows a direct glimpse on the present knowledge of other molecules involved. This is useful for a complete overview of the disease molecular mechanism/s and for planning future investigations. Data are collected in DAR, a database that is free for search and available at https://dar.biocomp.unibo.it .

Modeling ligand-macromolecular interactions as eigenvalue-based transition-state dissociation constants may offer insights into biochemical function of the resulting complexes

A ligand when bound to a macromolecule (protein, DNA, RNA) will influence the biochemical function of that macromolecule. This observation is empirical and attributable to the association of the ligand with the amino acids/nucleotides that comprise the macromolecule. The binding affinity is a measure of the strength-of-association of a macromolecule for its ligand and is numerically characterized by the association/dissociation constant. However, despite being widely used, a mathematically rigorous explanation by which the association/dissociation constant can influence the biochemistry and molecular biology of the resulting complex is not available. Here, the ligand-macromolecular complex is modeled as a homo- or hetero-dimer with a finite and equal number of atoms/residues per monomer. The pairwise interactions are numeric, empirically motivated and are randomly chosen from a standard uniform distribution. The transition-state dissociation constants are the strictly positive real part of all complex eigenvalues of this interaction matrix, belong to the open interval (0,1), and form a sequence whose terms are finite, monotonic, non-increasing and convergent. The theoretical results are rigorous, presented as theorems, lemmas and corollaries and are complemented by numerical studies. An inferential analysis of the clinical outcomes of amino acid substitutions of selected enzyme homodimers is also presented. These findings are extendible to higher-order complexes such as those likely to occur in vivo. The study also presents a schema by which a ligand can be annotated and partitioned into high- and low-affinity variants. The influence of the transition-state dissociation constants on the biochemistry and molecular biology of non-haem iron (Ⅱ)- and 2-oxoglutarate-dependent dioxygenases (catalysis) and major histocompatibility complex (Ⅰ) mediated export of high-affinity peptides (non-enzymatic association/dissociation) are examined as special cases.

Comparison Between Dichloroacetate and Phenylbutyrate Treatment for Pyruvate Dehydrogenase Deficiency

Pyruvate dehydrogenase (PDH) deficiency is caused by a number of pathogenic variants and the most common are found in the PDHA1 gene. The PDHA1 gene encodes one of the subunits of the PDH enzyme found in a carbohydrate metabolism pathway involved in energy production. Pathogenic variants of PDHA1 gene usually impact the α-subunit of PDH causing energy reduction. It potentially leads to increased mortality in sufferers. Potential treatments for this disease include dichloroacetate and phenylbutyrate, previously used for other diseases such as cancer and maple syrup urine disease. However, not much is known about their efficacy in treating PDH deficiency. Effective treatment for PDH deficiency is crucial as carbohydrate is needed in a healthy diet and rice is the staple food for a large portion of the Asian population. This review analysed the efficacy of dichloroacetate and phenylbutyrate as potential treatments for PDH deficiency caused by PDHA1 pathogenic variants. Based on the findings of this review, dichloroacetate will have an effect on most PDHA1 pathogenic variant and can act as a temporary treatment to reduce the lactic acidosis, a common symptom of PDH deficiency. Phenylbutyrate can only be used on patients with certain pathogenic variants (p.P221L, p.R234G, p.G249R, p.R349C, p.R349H) on the PDH protein. It is hoped that the review would provide an insight into these treatments and improve the quality of lives for patients with PDH deficiency.

HRD1 in human malignant neoplasms: Molecular mechanisms and novel therapeutic strategy for cancer

In tumor cells, the endoplasmic reticulum (ER) plays an essential role in maintaining cellular proteostasis by stimulating unfolded protein response (UPR) underlying stress conditions. ER-associated degradation (ERAD) is a critical pathway of the UPR to protect cells from ER stress-induced apoptosis and the elimination of unfolded or misfolded proteins by the ubiquitin-proteasome system (UPS). 3-Hydroxy-3-methylglutaryl reductase degradation (HRD1) as an E3 ubiquitin ligase plays an essential role in the ubiquitination and dislocation of misfolded protein in ERAD. In addition, HRD1 can target other normal folded proteins. In various types of cancer, the expression of HRD1 is dysregulated, and it targets different molecules to develop cancer hallmarks or suppress the progression of the disease. Recent investigations have defined the role of HRD1 in drug resistance in types of cancer. This review focuses on the molecular mechanisms of HRD1 and its roles in cancer pathogenesis and discusses the worthiness of targeting HRD1 as a novel therapeutic strategy in cancer.

Flavin Adenine Dinucleotide (FAD) Pegylated (PEG)-Complexes: Proof of Concept (PoC) of theranostic tool on a Murine Breast Cancer Model

Flavin adenine dinucleotide (FAD) plays a key role in an extensive range of cellular oxidation-reduction reactions, which is engaged in metabolic pathways. The purpose of this study was to realize pegylated flavins formulation, named FAD and FAD-PEG diacid complex as theranostic tool in cancer therapy. For this objective, a murine breast cancer model, which was induced by mouse-derived4T1 breast cancer cells was studied to assess the therapeutic efficacy of FAD (named NP1) and FAD-PEG diacid complex (named NP2). The cytokines were monitored to evaluate the serum inflammatory factors to develop the blood cell content of different groups of nude mice. The experimental model shows that an intravenous injection of FAD (NP1) can significantly reduce tumour volume, tumour index and thymus index, and decrease neutrophils (NE), monocytes (MO), eosinophils (EO), and basophils (BA). At the same time, the content of IL-1α, IL-12P70, TNF α, IL-1β and IL-6 was significantly reduced, and the content of IL-10 was significantly increased. These results provide the proof-of-concept for FAD as a smart adjuvant for cancer therapy and encourages their further development in the field of Nanomedicine.

Near-infrared (NIR) fluorescence-emitting small organic molecules for cancer imaging and therapy

We discuss recent advances made in the development of NIR fluorescence-emitting small organic molecules for tumor imaging and therapy.

Droplet-based microfluidics in biomedical applications

Droplet-based microfluidic systems have been employed to manipulate discrete fluid volumes with immiscible phases. Creating the fluid droplets at microscale has led to a paradigm shift in mixing, sorting, encapsulation, sensing, and designing high throughput devices for biomedical applications. Droplet microfluidics has opened many opportunities in microparticle synthesis, molecular detection, diagnostics, drug delivery, and cell biology. In the present review, we first introduce standard methods for droplet generation (i.e., passive and active methods) and discuss the latest examples of emulsification and particle synthesis approaches enabled by microfluidic platforms. Then, the applications of droplet-based microfluidics in different biomedical applications are detailed. Finally, a general overview of the latest trends along with the perspectives and future potentials in the field are provided.

Stem Cell Research Tools in Human Metabolic Disorders: An Overview

Metabolic disorders are very common in the population worldwide and are among the diseases with the highest health utilization and costs per person. Despite the ongoing efforts to develop new treatments, currently, for many of these disorders, there are no approved therapies, resulting in a huge economic hit and tension for society. In this review, we recapitulate the recent advancements in stem cell (gene) therapy as potential tools for the long-term treatment of both inherited (lysosomal storage diseases) and acquired (diabetes mellitus, obesity) metabolic disorders, focusing on the main promising results observed in human patients and discussing the critical hurdles preventing the definitive jump of this approach from the bench to the clinic.

Enzyme Therapy: Current Challenges and Future Perspectives

In recent years, enzymes have risen as promising therapeutic tools for different pathologies, from metabolic deficiencies, such as fibrosis conditions, ocular pathologies or joint problems, to cancer or cardiovascular diseases. Treatments based on the catalytic activity of enzymes are able to convert a wide range of target molecules to restore the correct physiological metabolism. These treatments present several advantages compared to established therapeutic approaches thanks to their affinity and specificity properties. However, enzymes present some challenges, such as short in vivo half-life, lack of targeted action and, in particular, patient immune system reaction against the enzyme. For this reason, it is important to monitor serum immune response during treatment. This can be achieved by conventional techniques (ELISA) but also by new promising tools such as microarrays. These assays have gained popularity due to their high-throughput analysis capacity, their simplicity, and their potential to monitor the immune response of patients during enzyme therapies. In this growing field, research is still ongoing to solve current health problems such as COVID-19. Currently, promising therapeutic alternatives using the angiotensin-converting enzyme 2 (ACE2) are being studied to treat COVID-19.

A Pegylated Flavin Adenine Dinucleotide PEG Complex to Boost Immunogenic and Therapeutic Effects in a Liver Cancer Model

Flavin adenine dinucleotide (FAD) is engaged in several metabolic diseases. Its main role is being a cofactor essential for the activity of many flavoproteins, which play a crucial role in electron transport pathways in living systems. The aim of this study was to apply a pegylated flavins formulation named FAD-PEG diacide complex as theranostic pathway in cancer therapy. For this purpose, a mouse liver cancer model induced by Hepa1-6 cells was used to evaluate the therapeutic efficacy of FAD (named NP1) and FAD-PEG diacide complex (named NP2). The cytokines were applied to screen the serum inflammatory factors, to establish the blood cell content of different groups of nude mice. The highlights follows that FAD formulations (NP1; NP2) significantly suppressed the tumor growth and reduced the tumor index without effects on the body weight of mice. Furthermore, NP2 significantly reduced the serum levels of cytokines IL-6, TNF-α and IL-12 (P70). The reported results provide the proof-of-concept for the synthesis of a smart adjuvant for liver cancer therapy and support their further development in the field of nanomedicine.

A novel metabolic disorder in the degradation pathway of endogenous methanol due to a mutation in the gene of alcohol dehydrogenase

BACKGROUND

A small amount of methanol is produced endogenously in the human body but it is efficiently metabolized by alcohol dehydrogenase (ADH) and other enzymes, and the products eliminated without harm. In this study, we present a new entity of inborn error of methanol metabolism due to a mutation in the ADH1C gene coding for the γ subunit that is part of several ADH isoenzymes.

RESULTS

This disorder was discovered in an 11.58-year-old boy. During one 9-month hospital admission, he had periods of 1-4 days during which he was comatose, and between these periods he was sometimes verbose and euphoric, and had ataxia, dysarthria. Following hemodialysis treatments, he became conscious and appeared healthy. Organ evaluations and his laboratory tests were normal. Toxicological evaluation of his blood showed a high methanol level [12.2 mg/dL (3.8 mmol/L), normal range up to 3.5 mg/dL (1.09 mmol/L) while the formaldehyde level was undetectable. The finding of liver function tests that were within normal limits, coupled with a normal eye examination and size of the liver, elevated blood methanol levels and an undetectable formaldehyde level, suggested ADH insufficiency. Adding zinc to the drug regimen 15 mg/daily dramatically reduced the patient's methanol level and alleviated the abnormal symptoms. When zinc supplementation was discontinued, the patient relapsed into a coma and hemodialysis was once again required. A homozygous mutation in ADH1C gene located at exon 3 was found, and both parents were heterozygous for this mutation.

CONCLUSION

Accumulation of methanol due to mutation in ADH1C gene may result in drunkenness and ataxia, and leads to coma. This condition can be successfully treated with zinc supplementation as the cofactor of ADH.

In silico study of peculiarities of metabolism of erythrocytes with glucosephosphate isomerase deficiency

Glucose phosphate isomerase (GPI) deficiency, the third most common cause of hereditary nonspherocytic hemolytic anemia, is associated with the mutation of the GPI gene. The results of the GPI deficiency are premature aging of erythrocytes, macrocytosis, reticulocytosis, minor splenomegaly, hyperbilirubinemia and hyperferritinemia, and hemolytic crisis under the influence of exogenous oxidants such as infections or drugs. Regarding the the lack of GPI correction drugs, the theoretical substantiation of supportive therapy based on system biology approaches that would allow the analysis of the relationships between numerical metabolic processes in a cell would be beneficial. The stoichiometric model of erythrocytes’ steady state metabolism, including the pathways of Embden-Meyerhof and pentose phosphate (PPP), purine metabolism cycles and glutathione synthesis, has been developed. To predict the redistribution of metabolic flows in erythrocytes under conditions of GPI deficiency, we used the flux balance analysis (FBA). In this approach, calculations of the elementary flux modes (EFMs) and the control-effective flux (CEF) have been performed. Using the CEF evaluation approach, effective profiles of enzymatic reactions depending on the degree of enzyme deficiency were obtained. It has been shown that these relationships can be the basis for future experimental studies. Analysis of the profiles of enzymatic reactions of metabolic networks suggests that erythrocytes are capable of metabolizing other substrates that contribute to overcoming the effects of energy stress in the case of enzymopathies. So, it is shown that erythrocytes can effectively use SAM and adenosine as alternative energy sources. It has been established that the GPI enzymopathy results in a decrease in the flow through the glycolysis and pentose phosphate pathway, resulting in a decrease in the content of such reducing agents as NADPH and GSH, ATP. The processes of the GSH synthesis from amino acids in the cell are shown to be suppressed. Decreased content of NADPH and GSH cause the premature aging of erythrocytes. The target therapeutic approaches that influence the behaviour of the metabolic network of erythrocytes are discussed.

Connections between metabolism and epigenetics in cancers

In the past half century, our version on cancer, from tumor initiation, growth, to metastasis, is dominated by genetic mutation. The importance of metabolism and epigenetics was not recognized until most recently. Extensive cell proliferation is one of the hallmarks of cancers. To support the energetic and anabolic demands of enhanced proliferation, tumors reprogram the pathways of nutrient procurement and metabolism. In this context, a new link between metabolic alterations and cancer progression has been unraveled over the last decade by the studies conducted in the area of cancer cell metabolism. Cancer cells are known to alter their metabolic profile during the course of tumorigenesis and metastasis thereby exhibiting a tightly regulated program of metabolic plasticity. Noteworthy, certain metabolic alteration are known to occur at the epigenetic level, thus making epigenetics and metabolism highly interwoven in a reciprocal manner. Metabolites that are generated during metabolic pathways, such as in glycolytic cycle and oxidative phosphorylation, serve as cofactors or substrates for the enzymatic reactions that catalyze the epigenetic modifications and transcriptional regulation. Several studies also indicate that the epigenome is sensitive to cellular metabolism. Since many of the metabolic alterations and consequently aberrated epigenetic regulation are common to a wide range of cancer types, they serve as promising targets for anti-cancer therapies. Here we discuss the latest findings in cancer cell metabolism, elucidating the major anabolic, catabolic and energetic demands required for sustaining cancer growth, and the influence of altered metabolism on epigenetics and vice versa. A comprehensive research pertaining to metabolomic profiling and epigenome interactors/mediators in malignant neoplasias is imperative in deciphering the potential targets that can be exploited for the development of robust anti-cancer therapies.

Towards comprehensive annotation of Drosophila melanogaster enzymes in FlyBase

The catalytic activities of enzymes can be described using Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. These annotations are available from numerous biological databases and are routinely accessed by researchers and bioinformaticians to direct their work. However, enzyme data may not be congruent between different resources, while the origin, quality and genomic coverage of these data within any one resource are often unclear. GO/EC annotations are assigned either manually by expert curators or inferred computationally, and there is potential for errors in both types of annotation. If such errors remain unchecked, false positive annotations may be propagated across multiple resources, significantly degrading the quality and usefulness of these data. Similarly, the absence of annotations (false negatives) from any one resource can lead to incorrect inferences or conclusions. We are systematically reviewing and enhancing the functional annotation of the enzymes of Drosophila melanogaster, focusing on improvements within the FlyBase (www.flybase.org) database. We have reviewed four major enzyme groups to date: oxidoreductases, lyases, isomerases and ligases. Herein, we describe our review workflow, the improvement in the quality and coverage of enzyme annotations within FlyBase and the wider impact of our work on other related databases.