Abstract

Stress can lead to various health problems. Exposure to stress is linked to several diseases including cancer, hypertension, diabetes, mental disorders, and heart attacks. Stress stimulates several pathways that produce free radicals, which increases oxidative stress. This results in functional and structural damage to organs, such as the brain, which is highly sensitive to oxidative stress Vitamin E is a naturally occurring potent antioxidant used for various purposes. The main purpose of the current study was to evaluate how vitamin E protects the brain and to what extent it affects antioxidant levels in rats subjected to two hours per day of immobilization stress, the form of stress with the strongest effect. The rats were immobilized by folding their limbs in and wrapping them in netting to prevent movement, while allowing their tails to be extended. The rats were then hung upside down. The effect of vitamin E was tested by intraperitoneally injecting rats with 40 mg/kg of vitamin E daily. Oxidative stress parameters were determined at the completion of the experiment. A dramatic decrease in malondialdehyde (MDA) levels and an increase in catalase (CAT), including glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD), has been shown by vitamin E in the brain. The effects of vitamin E were significantly higher in the acute and chronic stress groups than in the control group. Vitamin E can decrease oxidative stress in stressed rats, indicating that it exerts therapeutic and protective effects owing to its antioxidant properties.

Introduction

Stress is a normal factor in everyday vernacular and a fundamental aspect of the human condition. Millions of missed working days are attributed to stress, which is acknowledged globally as the main contributor to chronic illnesses (e.g., Am. Psychol. Assoc. 2019, UK Health Saf. Executive 2019). It has been reported that stress affects every aspect of life. Furthermore, stress is known to have both direct and indirect negative effects on health via changes in neuroendocrine and autonomic functions (O’Connor et al., 2021).

Activation of the HPA axis, which causes an increase in corticosterone levels in the brain, is a key mechanism linked to stress-induced behavioral problems. Rapid depolarization caused by elevated corticosterone levels causes glutamate to be released into limbic and cortical areas. An increase in metabolic rate and mitochondrial dysfunction may result from glutamate overproduction. An increase in the metabolic rate results in a conflict between the generation of ROS and antioxidant system activity, which causes the generation of more free radicals. Nucleic acids, proteins, and lipids are just a few cellular components that oxidatively damage these free radical species oxidatively damage (Samarghandian et al., 2017).

Free radicals are associated with oxidative stress. Free radicals are highly reactive with unpaired electrons and atoms. An increase in the levels of antioxidants and free radicals can lead to oxidative stress.

Conclusion

Levels of the antioxidants GSH, SOD, and CAT in the brain were significantly higher in the vitamin E group than in the acute and chronic stress groups (controls). Vitamin E also significantly reduced MDA levels and oxidative stress in stressed rats. These findings suggest that vitamin E can prevent and relieve stress.

Abstract

Several microRNAs (miRNAs), including miR-23 and miR-27a have been reportedly involved in regulating myelination in the central nervous system. Although miR-23 and miR-27a form clusters in vivo and the clustered miRNAs are known to perform complementary functions, the role of these miRNA clusters in myelination has not been studied. To investigate the role of miR-23-27-24 clusters in myelination, we generated miR-23-27-24 cluster knockout mice and evaluated myelination in the brain and spinal cord. Our results showed that 10-week-old knockout mice had reduced motor function in the hanging wire test compared to the wild-type mice. At 4 weeks, 10 weeks, and 12 months of age, knockout mice showed reduced myelination compared to wild-type mice. The expression levels of myelin basic protein and myelin proteolipid protein were also significantly lower in the knockout mice compared to the wild-type mice. Although differentiation of oligodendrocyte progenitor cells to oligodendrocytes was not inhibited in the knockout mice, the percentage of oligodendrocytes expressing myelin basic protein was significantly lower in 4-week-old knockout mice than that in wild-type mice. Proteome analysis and western blotting showed increased expression of leucine-zipper-like transcription regulator 1 (LZTR1) and decreased expression of R-RAS and phosphorylated extracellular signal-regulated kinase 1/2 (pERK1/2) in the knockout mice. In summary, loss of miR-23-27-24 clusters reduces myelination and compromises motor functions in mice. Further, LZTR1, which regulates R-RAS upstream of the ERK1/2 pathway, a signal that promotes myelination, has been identified as a novel target of the miR-23-27-24 cluster in this study.

Introduction

In the central nervous system (CNS), myelin, produced by oligodendrocytes, supports axonal metabolism and allows for rapid transmission of action potentials along axons [1–3]. In demyelinating conditions such as multiple sclerosis or spinal cord injury, myelin is lost and axons degenerate, resulting in permanent loss of function. Remyelination in these demyelinating conditions remains a challenge. Developmental myelination and remyelination have the common goal of attaching myelin sheaths to axons [4]. In addition, there is a common mechanism underlying developmental myelination and remyelination, and remyelination is considered as “rerunning” of myelination [4]. Therefore, understanding the mechanism underlying myelination will help in developing novel strategies for remyelination in various disease conditions. Normal myelination is a multistep process in which oligodendrocyte differentiation and initiation of myelination are tightly regulated [5]. Previous studies have shown that several genes, transcription factors, and pathways are involved in oligodendrocyte progenitor cell (OPC) proliferation and oligodendrocyte differentiation, maturation, and myelination [6–8]. Furthermore, recent studies have shown that microribonucleic acids (miRNAs) play important roles in regulating myelination [9–15].

Results

3.1. Expression of the miR-23-27-24 Cluster in the CNS
KO mice were slightly smaller than wild-type mice but were born and grew without morphological abnormalities (Figure 1(a)). Compared to 10-week-old wild-type mice, the expression of all miRNAs in the miR-23-27-24 cluster was significantly lower in the KO mice, both in the spinal cord and brain () (Figures 1(b) and 1(c) and Table 1).

Next, we compared the expression of the miR-23-27-24 cluster in the spinal cord of mice at different ages (4 weeks, 10 weeks, and 12 months of age). For all miRNAs in the miR-23-27-24 cluster, the expression levels in 10- and 12- week-old wild-type mice were significantly higher than those in 4-week-old wild-type mice (p < 0:001) (Figure 2). The expression of miR-23a in 12-month-old wild-type mice was significantly lower than that in 10-week-old wild-type mice (p < 0:001) (Figure 2(a)), but there were no significant differences in the expression of other miRNAs (Figures 2(b)–2(e)). The expression of all miRNAs in KO mice was significantly lower than that in wild-type mice at all ages (Table 2).

SUMMARY

The coordination of chloroplast and nuclear genome status is critical for plant cell function. Here, we report that Arabidopsis CHLOROPLAST AND NUCLEUS DUAL-LOCALIZED PROTEIN 1 (CND1) maintains genome stability in the chloroplast and the nucleus. CND1 localizes to both compartments, and complete loss of CND1 results in embryo lethality. Partial loss of CND1 disturbs nuclear cell-cycle progression and photosynthetic activity. CND1 binds to nuclear pre-replication complexes and DNA replication origins and regulates nuclear genome stability. In chloroplasts, CND1 interacts with and facilitates binding of the regulator of chloroplast genome stability WHY1 to chloroplast DNA. The defects in nuclear cell-cycle progression and photosynthesis of cnd1 mutants are respectively rescued by compartment-restricted CND1 localization. Light promotes the association of CND1 with HSP90 and its import into chloroplasts. This study provides a paradigm of the convergence of genome status across organelles to coordinately regulate cell cycle to control plant growth and development.

INTRODUCTION

Chloroplasts in plants and algae have an endosymbiotic origin: over 2 billion years ago, a photosynthetic cyanobacterium-like organism was stably engulfed by a heterotrophic unicellular eukaryote.1 This initial event was followed over the course of evolution by massive gene transfer from the green prokaryote genome to the host-cell nucleus, leading to the complete dependency of the endosymbiont on its surrounding cells and the generation of a novel type of organism, photosynthetic eukaryotes.2 The development of higher plants requires the tight coordination of chloroplast development from undifferentiated proplastids in meristematic cells or from etioplasts, which differentiate from proplastids when seeds germinate in darkness. In addition to being the site of photosynthesis in leaf mesophyll cells, chloroplasts house essential metabolic pathways and contribute to storage and pigmentation in specialized cells.3

Eukaryote genomes are organized into multiple chromosomes whose replication initiates from numerous origins and is strictly regulated.4 To maintain genome integrity and stability, genomic DNA must be replicated completely and accurately, but also only once during the S phase of the cell cycle. The formation of a pre-replication complex (pre-RC) is required for the subsequent ordered assembly of replication factors such as the Origin Recognition Complex (Orc), Cell Division Cycle6 (Cdc6) in budding yeast (Saccharomyces cerevisiae) or its ortholog CDC18 in fission yeast (Schizosaccharomyces pombe), chromatin licensing and DNA replication factor 1 (CDT1), and Mini Chromosome Maintenance (MCM) proteins (MCM2–7).5 MCM proteins are essential replication initiation factors that were originally identified as proteins required for minichromosome maintenance, plasmid replication, or cell-cycle progression in yeast.6 Indeed, cell-cycle checkpoints are crucial for genome integrity, as they stop cell-cycle progression upon DNA damage until repairs have been completed. Such mechanisms are particularly important in plants, which endure daily exposure to DNA-damaging agents such as light and reactive oxygen species (ROS).7

RESULTS

CND1 is a nucleus and chloroplast dual-localized protein
To understand the functional coordination between the chloroplast and nucleus, we systematically screened proteins with predicted chloroplast and nucleus dual localization by combining bioinformatics and proteomics analyses. We focus here on one such putative chloroplast and nucleus dual-localized protein, encoded by the nuclear gene At1g32730 that we named CHLOROPLAST AND NUCLEUS DUAL-LOCALIZED PROTEIN 1 (CND1). CND1 contains four predicted functional domains: two targeting domains, consisting of an N-terminal chloroplast transit peptide (cTP) (amino acids [aa] 1–65) based on TargetP prediction27 and a nuclear localization sequence (NLS) containing the amino acid motif KRKK28; a zinc finger domain (ZF); and the domain of unknown function DUF702 (Figure 1A ).

Summary

β-arrestin plays a key role in G protein-coupled receptor (GPCR) signaling and desensitization. Despite recent structural advances, the mechanisms that govern receptor-β-arrestin interactions at the plasma membrane of living cells remain elusive. Here, we combine single-molecule microscopy with molecular dynamics simulations to dissect the complex sequence of events involved in β-arrestin interactions with both receptors and the lipid bilayer. Unexpectedly, our results reveal that β-arrestin spontaneously inserts into the lipid bilayer and transiently interacts with receptors via lateral diffusion on the plasma membrane. Moreover, they indicate that, following receptor interaction, the plasma membrane stabilizes β-arrestin in a longer-lived, membrane-bound state, allowing it to diffuse to clathrin-coated pits separately from the activating receptor. These results expand our current understanding of β-arrestin function at the plasma membrane, revealing a critical role for β-arrestin preassociation with the lipid bilayer in facilitating its interactions with receptors and subsequent activation.

Introduction

G protein-coupled receptors (GPCRs) are implicated in virtually every physiological process and are major drug targets.1,2 Following agonist-mediated GPCR activation and phosphorylation by G protein-coupled-receptor kinases (GRKs), β-arrestins translocate from the cytosol to bind agonist-occupied, phosphorylated receptors on the plasma membrane. There are four arrestins—two visual arrestins (also known as arrestin 1 and 4), β-arrestin 1 (βArr1) (arrestin 2), and β-arrestin 2 (βArr2) (arrestin 3).

By interacting with the receptor core, β-arrestins mediate rapid signal desensitization.3 In addition, β-arrestins trigger receptor internalization via interaction with the adaptor protein 2 (AP2) and clathrin heavy chain.4 Moreover, β-arrestins have been proposed to mediate “non-classical” G protein-independent effects,5 providing a mechanism for “biased” signaling.6 This diversity of functions has been linked to multiple conformations in receptor-arrestin complexes revealed by structural and biophysical studies with purified proteins.7,8,9,10,11,12,13,14,15,16,17 Furthermore, recent findings of prolonged β-arrestin activation18,19,20 suggest that β-arrestin signaling might be more complex than previously thought. However, how this complexity operates on the plasma membrane of living cells remains largely unknown.

Here, we combined an innovative multicolor single-molecule microscopy approach21,22 with molecular dynamics (MD) simulations to dissect the sequence of events in receptor-β-arrestin interactions at the plasma membrane of living cells with ∼20 nm spatial and 30 ms temporal resolution.21,22 Our results reveal that β-arrestin binds directly to the lipid bilayer, allowing it to transiently interact with receptors via lateral diffusion, and reaches clathrin-coated pits (CCPs) separately from the activating receptor.

Results

Single-molecule imaging reveals spontaneous membrane translocation and lateral diffusion of βArr2
As a main model, we chose βArr2 and the β2-adrenergic receptor (β2AR), a prototypical family-A GPCR that regulates numerous physiological processes.23,24 To investigate the behavior of individual βArr2 and β2AR molecules on the plasma membrane of living cells, we labeled them with two distinct organic fluorophores via fusion of Halo25 and SNAP26 tags to their C and N termini, respectively (Figure 1A). Both constructs were transiently expressed at low physiological levels in Chinese hamster ovary (CHO) cells, which have no detectable β1AR/β2AR.27 Both βArr2-Halo and SNAP-β2AR constructs are functional; βArr2-Halo binds receptors and mediates receptor internalization to a similar extent as wild-type (WT) βArr2, and co-localizes with internalized receptors in endosomes (Figures S1A–S1D; see STAR Methods for details). CHO cells were then labeled with saturating concentrations of both organic fluorophores (Figure S1E) and were simultaneously imaged by fast multicolor total internal reflection fluorescence (TIRF) microscopy combined with single-particle tracking22 (Figure 1B; Videos S1 and S2); unspecific labeling was <1% (Figure S1F). We additionally visualized CCPs by co-transfection of GFP-labeled clathrin light chain. Data were acquired both under basal conditions and after early (2–7 min) and late (8–15 min) stimulation with the β-adrenergic full agonist isoproterenol (Iso). An excess of 5.8 million individual molecular trajectories were acquired and analyzed in this study. Numbers of trajectories and particle densities in the analyzed groups are given in Table S1.

Abstract

Keywords

Introduction

Methods

Results

Discussion

Conclusion

Author contributions

Availability of data

Conflicts of interest

Acknowledgements

References

Article Info

Figures

Tables

Related Articles

Abstract

Introduction It has been suggested that the future of diagnostic imaging relies on engagement in research and evidence-based practice. This implies a role transition from a clinical radiographer to a clinical radiographer-researcher. Clinical radiographers’ stimuli for engaging in research in Nordic countries are unknown. This study aimed to address this gap.

Methods
Cross-sectional data collection via an online questionnaire on facilitators for and barriers to participation in radiography research was carried out among 507 clinical radiographers in public healthcare in the Nordic countries: Denmark, Finland, Norway and Sweden.

Results
Support from colleagues (odds ratio [OR] 2.62) and other professionals (OR 2.74), and self-esteem in research skills (OR ≥ 2.21), were facilitators for radiography research. Lack of knowledge and skills to conduct research (OR 2.48) was revealed to hinder radiographers’ participation in research. The absence of a radiography research culture in the workplace explained non-participation in research (OR 1.75).

Introduction 

It has been suggested that the future of diagnostic imaging relies on engagement in research and evidence-based practice (EBP).1e4 While radiologists and physicists have a long tradition of conducting research in medicine and radiation physics, radiographers are still in the initial stages of radiography research, but academic development of radiographers is ongoing while they usually perform research studies alongside university teaching.5e7 Radiography research has been found to address, for example, radiographic technology and patient well-being and care.8,9 There are several reasons to investigate clinical radiographers’ stimuli for engaging in radiography research. One is radiographers’ responsibility for and expertise in patient care in diagnostic imaging.

Abstract

     Agriculture plays a significant part in India due to their population growth and increased food demands. Hence, there is a need to enhance the yield of crop. One of these important effects on low crop yields is diseases caused by bacteria, fungi and viruses. This can be prevented and handled by means of applying plant disease detection approaches. Machine learning techniques will be employed in the process of disease identification on plants as it mostly applies information themselves and offers fabulous techniques for detection of plant diseases. Methods based on Machine learning can be employed for the identification of diseases because it mainly applies on data superiority outcomes for specified task. In this approach, a comprehensive review has been made on the various techniques employed in plant disease detection using artificial intelligence (AI) based machine learning and deep learning techniques. Likewise, deep learning has also gained a great deal of significance in offering better performance outcome for detecting plant disease in the computer vision field. The deep learning advancements were employed to a range of domains that leads to great attainment in the machine learning and computer vision areas. The comparative study is made in terms of machine and deep learning techniques and their performance and usage in various research papers is related to show the effectiveness of deep learning model over machine learning model. In order to prevent major crop losses, the deep learning technique can be used to detect the leaf diseases from captured images.

Introduction

     The advancements of IoT, AI and the Unmanned Aerial Vehicles are integrated together to provide the support to agricultural fields to detect the plant leaf diseases and report that properly to the respective individuals with proper accuracy ranges. In this modern civilization, nobody is interested in farming and agriculture due to the hurdles the farmers are facing every day. So, that all young generation people are switch over their residence to modern cities to lead a safe life and avoid such agriculture field hurdles. The issue of the proficient plant diseases protection is closely linked to viable change in climate and agriculture [13]. Studies show that climate change may vary pathogenic stages and rates; host resistance may also be altered, leading to physiological variations in host-pathogen co-operations [23]. The actuality that nowadays, diseases more freely transferred around the globe than ever before complicates the situation. New diseases may occur where they have not been identified previously and, inherently, where local expertise to combat them is not available [27] (see Table 1).

Conclusion

     An extensive research study is conceded out on various kinds of machine and deep learning techniques for plant disease recognition and classification. After this, other techniques of classification in machine learning might be employed for may be used for plants disease detection and in the intellect of aiding the farmers an automatic disease detection of all kinds of disease in the crop that were to be detected. This analysis discusses various approaches of DL for the plant diseases detection. Furthermore, several techniques/mappings were summarized for recognizing the disease symptoms. Here the development of deep learning technologies in recent years for the identification of plant leaf diseases. We anticipate that this work will be a useful tool for scientists looking into plant disease detection. Also, a comparative study is also made between machine and deep learning techniques. Though a great deal of noteworthy progress was noticed in recent years, there were still some research gaps that should be addressed and to implement effective techniques for plant disease detection.

Highlights

Abstract

Graphical abstract

Keywords

1. Introduction

2. Materials and methods

3. Results

4. Discussion

Credit authorship contribution statement

Appendix A. Supplementary material

References

Background: Eponyms are commonly used in medicine, but there are no specific studies of the use of eponyms in clinical chemistry. Methods: Clinical chemistry eponyms were manually collected from books, review articles and journal articles from 1847 through 2020. Eponym usage was examined by searching titles and abstracts in PubMed. Custom Python scripts were used to first permute eponyms into multiple forms, and then to search PubMed using Biopython. The eponyms identified in PubMed were further focused on 2 clinical chemistry journals Clinica Chimica Acta [CCA] and Clinical Chemistry [CCJ]. Results: The manual collection identified >300 eponyms in clinical chemistry. The Biopython search of PubMed identified a subset of 97 unique eponyms in 33,232 articles. PubMed identified 26 eponyms used in 130 CCA articles; whereas a full-text search identified 1187 articles. In comparison, PubMed identified 36 eponyms used in 158 CCJ articles; whereas a full-text CCJ search identified 708 articles. PubMed shows that the journals CCA and CCJ had a peak number of eponym citations in 1977 followed by a steady decline. Conclusions: Eponyms have been frequently used in clinical chemistry with 97 eponyms in common use in PubMed. Overall, the use of clinical chemistry eponyms appears to be declining.

1. Introduction

Naming chemical reactions, chemical reagents, mathematical equations, units, coefficients, constants, laws, diseases, and clinical signs and symptoms, after people (eponyms), places (toponyms) or mythical beings (mythonyms) is not uncommon, and there are a number of compendia of medical eponyms [1–3]. Likewise, in the field of clinical pathology there are compendia of eponyms used in hematology [4], and microbiology [5], but we are not aware of a compendium of eponyms relating specifically to clinical chemistry. There are some general works published at the end of the 19th century and the beginning of the 20th century that list named “tests (reagents)” [6], reagents and reactions relevant to physiological-pathological chemistry [7], pharmacology/ toxicology [8], “tests and reagents known by their author’s names” of practical utility for “the busy chemist, microscopist, and pharmacist” [9], and reactions and reagents for the doctor, analyst, pharmacist, and chemist [10]. Although these lists contain some clinical chemistry eponyms, by and large, they are general lists with an emphasis on chemistry tests and reagents. Eponyms abound in clinical chemistry, including some derived from general laboratory sciences (e.g., Erlenmeyer flask), or from the intersection of clinical chemistry with physics (e.g., Rayleigh scattering), biochemistry (e.g., Michaelis-Menten kinetics), and statistics (e.g., Kruskall-Wallis test). Recently, we examined the natural history of the Malloy-Evelyn Reaction, and traced the coinage and chronology of the adoption of this eponym [11]. We have now extended our study of eponyms and have compiled a list of eponyms relating specifically to clinical chemistry methods, tests, reagents, apparatus, tables, formulae, and coefficients, and examined their usage in clinical chemistry over time.

Abstract

Introduction

Species Implicated in Human Infestations

Biology and Life Cycle

Epidemiology of C. lectularius and C. hemipterus

Clinical Relevance

Control

Laboratory Collection, Identification, and Reporting

Specimen collection and handling

Morphologic features of adults and nymphs

Identification of the species of cimicids reported from humans

Reporting

References

Abstract

The world has experienced a major global resurgence of bed bug infestations over the past 2 decades. While bed bugs do not serve as vectors of disease, their bites and household infestations result in significant psychological distress, clinical manifestations, and economic costs. Most human bed bug infestations are caused by the “common bed bug,” Cimex lectularius, or the “tropical bed bug,” C. hemipterus. Zoonotic cimicids also occasionally feed on humans. Bites are the most commonly reported manifestation of infestations, although findings may be subtle and overlooked for some time. The bugs can be submitted to the laboratory for identification, and therefore, clinical microbiologists should be familiar with their key identifying features and how they can be differentiated from similar-appearing arthropods. This review covers the biology and epidemiology of bed bugs; aspects of laboratory collection, identification, and reporting; and the clinical implications of bed bug infestations.

Introduction

“Good night, sleep tight; don’t let the bed bugs bite.” This version of the well-known rhyme was first published in 1896 in the book What They Say in New England by Clifton Johnson, but variations of this verse can be found in the literature in the decades before [1]. While a seemingly innocent bedtime rhyme, it reflects the reality of life in colonial New England, in which residents went to bed hoping not to be bitten by these blood-sucking pests while they were sleeping. We now know that bed bugs have long been associated with human habitats, being found in references throughout history and from archaeological sites dating back 3,500 years [2]. Bed bugs were thought to have spread throughout Asia and Europe in the early centuries of the Common Era, and later traveled to the Americas aboard ships of early European sailors [3]. By the 1900s, bed bugs were estimated to be in 1/3 of the dwellings in European cities and disproportionately affected those living in poor, crowded neighborhoods. While bed bugs do not serve as vectors of disease, their bites and household infestations result in psychological distress, a range of unpleasant clinical manifestations, property loss, and other substantial economic costs [4, 5, 6]. It was only with the widespread household use of dichloro-diphenyl-trichloroethane (DDT) and other potent long-lasting pesticides throughout the 1940s to 1960s that the prevalence of bed bug infestations significantly decreased worldwide [3].
Unfortunately, the world is now experiencing a major resurgence in bed bug infestations, with an explosion of reports beginning around the turn of the century [4, 7]. Although the exact cause of this resurgence is unknown, it is thought to be due to multiple factors, including widespread resistance to commonly used pesticides, increased domestic and international travel, and the decline in public health pest control programs that occurred in the latter half of the 1900s [8].

Highlights

Abstract

Graphical abstract

Abbreviations

Keywords

1. Introduction

2. De novo identification of mitochondrial proteins

2.1. In silico strategies

2.2. Experimental strategies

2.3. Integrative biology strategies

3. From proteins to functions: deorphanizing the unknown

3.1. In silico strategies

3.2. Experimental strategies

4. Perspectives

CRediT authorship contribution statement

Declaration of Competing Interest

Acknowledgments

References

Abstract

Human mitochondria are complex and highly dynamic biological systems, comprised of over a thousand parts and evolved to fully integrate into the specialized intracellular signaling networks and metabolic requirements of each cell and organ. Over the last two decades, several complementary, top-down computational and experimental approaches have been developed to identify, characterize and modulate the human mitochondrial system, demonstrating the power of integrating classical reductionist and discovery-driven analyses in order to de-orphanize hitherto unknown molecular components of mitochondrial machineries and pathways. To this goal, systematic, multiomics-based surveys of proteome composition, protein networks, and phenotype-to-pathway associations at the tissue, cell and organellar level have been largely exploited to predict the full complement of mitochondrial proteins and their functional interactions, therefore catalyzing data-driven hypotheses. Collectively, these multidisciplinary and integrative research approaches hold the potential to propel our understanding of mitochondrial biology and provide a systems-level framework to unraveling mitochondria-mediated and disease-spanning pathomechanisms.

1. Introduction

Mitochondria are essential organelles for cellular and organismal life in virtually all eukaryotes (Fig. 1). Present-day human mitochondria originated from the integration of an endosymbiotic α-proteobacterium into a host cell, therefore exchanging their independence for a semi-autonomous life [1,2]. By the late 1990s, comparative genomics analyses of α-proteobacteria genomes and quantitative two-dimensional gels of highly purified mitochondria suggested that the mammalian mitochondrial proteome consists of ∼1,000–1,500 distinct proteins [3,4]. The majority of those proteins derive from the eukaryotic genome, whereas the prokaryotic genome was significantly reduced during the transition from endosymbiotic bacterium to organelle [2] (Fig. 2A). To date, only a handful of protein-coding genes – thirteen in mammals – are still retained in the mitochondrial DNA (mt-DNA) of almost all eukaryotes. Therefore, most of the mitochondrial proteome is encoded from the nuclear genome, translated in the cytosol, and then targeted and imported into the organelle.

Strikingly, only 1% of mammalian mitochondrial proteins are allocated to ATP synthesis, highlighting that the organelle’s functions reach far beyond energy production (Fig. 1). Indeed, mitochondria are at the core of multiple cellular pathways, including the biosynthesis of precursors for cholesterol, estrogen, testosterone and hemoglobin; the regulation of redox and ion homeostasis; the activation of antiviral responses and cell death. Adding an additional layer of complexity, mitochondrial functions are tied to the specialized tasks and physiology of different cell types, tissues, and organisms [5]. For instance, only between 40–70 % of the human mitochondrial proteome is conserved in commonly used model systems such as unicellular eukaryotes (e.g. S. cerevisiae) and invertebrates (e.g. C. elegans, D. melanogaster) (Fig. 2B). Furthermore, over 15 % of the mitochondrial system shows tissue-specificity [6] and profound differences even among cell types of the same tissue [6,7].

Abstract

Keywords

1. Introduction

2. What is life?

3. What is a virus?

4. Do any virus-like systems achieve closure to efficient causation?

5. Conclusion

Declaration of Competing Interest

Acknowledgements

Appendix A. Supplementary data

References

Abstract

Whether or not viruses are alive remains unsettled. Discoveries of giant viruses with translational genes and large genomes have kept the debate active. Here, a fresh approach is introduced, based on the organisational definition of life from within systems biology. It views living as a circular process of self-organisation and self-construction which is ‘closed to efficient causation’. How information combines with force to fabricate and organise environmentally obtained materials, given an energy source, is here explained as a physical embodiment of informational constraint. Comparing a general virus replication cycle with Rosen’s -system shows it to be linear, rather than closed. Some viruses contribute considerable organisational information, but so far none is known to supply all required, nor the material nor energy necessary to complete their replication cycle. As a result, no known virus replication cycle is closed to efficient causation: unlike cellular obligate parasites, viruses do not match the causal structure of an -system. Analysis based in identifying a Markov blanket in causal structure proved inconclusive, but using Integrated Information Theory on a Boolean representation, it was possible to show that the causal structure of a virocell is not different from that of the host cell.

Introduction

The first half of 2020 has seen one particular virus (SARS-Cov2) dominate world news, so much that viruses appear to be at the forefront of public interest in biological research and in this context an old debate has reemerged: “Are viruses alive?”. According to an informal survey (Racaniello, 2014), expert opinion remains divided roughly a third each between yes, no and don’t know. This is not surprising given that the debate seems still to be resolved. Eleven years ago, an emphatic statement was made against including viruses among the living (Moreira and Lopez-Garcia, 2009), quickly countered by (sometimes indignant) responses of matching boldness (Claverie and Ogata (2009); Hegde et al. (2009)) and more nuanced responses (e.g. Forterre (2010b)). The discovery of giant viruses(Raoult and Forterre, 2008; Abergel et al., 2015; Claverie and Abergel, 2018), especially the Pandoraviruses, having genome sizes reaching that of parasitic eukaryotes (Nad`ege et al., 2013) and Tupanviruses with their batteries of translational genes (Abrah˜ao and et al., 2018; Rodrigues et al., 2020) has further stirred the debate (e.g. Claverie and Abergel (2010); Abergel et al. (2015); Brandes and Linial (2019)). It also attracted philosophers of science who having analysed the debate, concluded that it is misguided (van Regenmortel, 2016; Koonin and Starokadomskyy, 2016). Whether or not viruses belong within the category of living has again become highly topical and contentious.