Diel Cycle Proteomics: Illuminating Molecular Dynamics in Purple Bacteria for Optimized Biotechnological Applications

Circadian rhythms, characterized by approximately 24 h cycles, play a pivotal role in enabling various organisms to synchronize their biological activities with daily variations. While ubiquitous in Eukaryotes, circadian clocks remain exclusively characterized in Cyanobacteria among Prokaryotes. These rhythms are regulated by a core oscillator, which is controlled by a cluster of three genes: kaiA, kaiB, and kaiC. Interestingly, recent studies revealed rhythmic activities, potentially tied to a circadian clock, in other Prokaryotes, including purple bacteria such as Rhodospirillum rubrum, known for its applications in fuel and plastic bioproduction. However, the pivotal question of how light and dark cycles influence protein dynamics and the expression of putative circadian clock genes remains unexplored in purple non-sulfur bacteria. Unraveling the regulation of these molecular clocks holds the key to unlocking optimal conditions for harnessing the biotechnological potential of R. rubrum. Understanding how its proteome responds to different light regimes-whether under continuous light or alternating light and dark cycles-could pave the way for precisely fine-tuning bioproduction processes. Here, we report for the first time the expressed proteome of R. rubrum grown under continuous light versus light and dark cycle conditions using a shotgun proteomic analysis. In addition, we measured the impact of light regimes on the expression of four putative circadian clock genes (kaiB1, kaiB2, kaiC1, kaiC2) at the transcriptional and translational levels using RT-qPCR and targeted proteomic (MRM-MS), respectively. The data revealed significant effects of light conditions on the overall differential regulation of the proteome, particularly during the early growth stages. Notably, several proteins were found to be differentially regulated during the light or dark period, thus impacting crucial biological processes such as energy conversion pathways and the general stress response. Furthermore, our study unveiled distinct regulation of the four kai genes at both the mRNA and protein levels in response to varying light conditions. Deciphering the impact of the diel cycle on purple bacteria not only enhances our understanding of their ecology but also holds promise for optimizing their applications in biotechnology, providing valuable insights into the origin and evolution of prokaryotic clock mechanisms.

Dehydroamino acid residues in bioactive natural products

Covering: 2000 to up to 2023α,β-Dehydroamino acids (dhAAs) are unsaturated nonproteinogenic amino acids found in a wide array of naturally occurring peptidyl metabolites, predominantly those from bacteria. Other organisms, such as fungi, higher plants and marine invertebrates, have also been found to produce dhAA-containing peptides. The α,β-unsaturation in dhAAs has profound effects on the properties of these molecules. They display significant synthetic flexibility, readily undergoing reactions such as Michael additions, transition-metal-catalysed cross-couplings, and cycloadditions. These residues in peptides/proteins also exhibit great potential in bioorthogonal applications using click chemistry. Peptides containing contiguous dhAA residues have been extensively investigated in the field of foldamers, self-assembling supermolecules that mimic biomacromolecules such as proteins to fold into well-defined conformations. dhAA residues in these peptidyl materials tend to form a 2.05-helix. As a result, stretches of dhAA residues arrange in an extended conformation. In particular, peptidyl foldamers containing β-enamino acid units display interesting conformational, electronic, and supramolecular aggregation properties that can be modulated by light-dependent E-Z isomerization. Among approximately 40 dhAAs found in the natural product inventory, dehydroalanine (Dha) and dehydrobutyrine (Dhb) are the most abundant. Dha is the simplest dehydro-α-amino acid, or α-dhAA, without any geometrical isomers, while its re-arranged isomer, 3-aminoacrylic acid (Aaa or ΔβAla), is the simplest dehydro-β-amino acid, or β-enamino acid, and displays E/Z isomerism. Dhb is the simplest α-dhAA that exhibits E/Z isomerism. The Z-isomer of Dhb (Z-Dhb) is sterically favourable and is present in the majority of naturally occurring peptides containing Dhb residues. Dha and Z-Dhb motifs are commonly found in ribosomally synthesized and post-translationally modified peptides (RiPPs). In the last decade, the formation of Dha and Dhb motifs in RiPPs has been extensively investigated, which will be briefly discussed in this review. The formation of other dhAA residues in natural products (NPs) is, however, less understood. In this review, we will discuss recent advances in the biosynthesis of peptidyl NPs containing unusual dhAA residues and cryptic dhAA residues. The proposed biosynthetic pathways of these natural products will also be discussed.

Metasurface for Engineering Superimposed Ince-Gaussian Beams

Ince-Gaussian beams (IGBs) are the third complete family of exact and orthogonal solutions of the paraxial wave equation and have been applied in many fields ranging from particle trapping to quantum optics. IGBs play a very important role in optics as they represent the exact and continuous transition modes connecting Laguerre-Gaussian and Hermite-Gaussian beams. The method currently in use suffers from the high cost, complexity, and large volume of the optical system. The superposition of IGBs can generate complicated structured beams with multiple phase and polarization singularities. A metasurface approach is proposed to realizing various superpositions of IGBs without relying on a complicated optical setup. By superimposing IGBs with even and odd modes, multiple phase, and polarization singularities are observed in the resultant beams. The phase and polarization singularities are modulated by setting the initial phase in the design and controlling the incident linear polarization. The compactness of the developed metasurface devices and the unique properties of the generated beams have the potential to impact many practical applications such as particle manipulation, orbital angular momentum spectrum manipulation, and optical communications.

Water Quality Assessment and Decolourisation of Contaminated Ex-Mining Lake Water Using Bioreactor Dye-Eating Fungus (BioDeF) System: A Real Case Study

The environmental conditions of a lake are influenced by its type and various environmental forces such as water temperature, nutrients content, and longitude and latitude to which it is exposed. Due to population growth and development limits, former mining lakes are being converted to more lucrative land uses like those of recreational zones, agriculture, and livestock. The fungus Ganoderma lucidum has the potential to be utilised as a substitute or to perform synergistic bacteria-coupled functions in efficient contaminated lake water treatment. The purpose of this paper is to evaluate the water quality and water quality index (WQI) of an ex-mining lake named Main Lake in the Paya Indah Wetland, Selangor. Furthermore, the current work simulates the use of a Malaysian fungus in decolourising the contaminated ex-mining lake by the BioDeF system in a 300 mL jar inoculated with 10% (v/v) of pre-grown Ganoderma lucidum pellets for 48 h. According to the results, the lake water is low in pH (5.49 ± 0.1 on average), of a highly intense dark brownish colour (average reading of 874.67 ± 3.7 TCU), and high in iron (Fe) content (3.2422 ± 0.2533 mg/L). The water quality index of the lake was between 54.59 and 57.44, with an average value of 56.45; thus, the water was categorized as Class III, i.e., under-polluted water, according to the Malaysian Department of Environment Water Quality Index (DOE-WQI, DOE 2020). The batch bioreactor BioDeF system significantly reduced more than 90% of the water's colour. The utilization of Ganoderma lucidum as an adsorbent material offers a variety of advantages, as it is easily available and cultivated, and it is not toxic.

Imaging Threading Dislocations and Surface Steps in Nitride Thin Films Using Electron Backscatter Diffraction

Extended defects, like threading dislocations, are detrimental to the performance of optoelectronic devices. In the scanning electron microscope, dislocations are traditionally imaged using diodes to monitor changes in backscattered electron intensity as the electron beam is scanned over the sample, with the sample positioned so the electron beam is at, or close to the Bragg angle for a crystal plane/planes. Here, we use a pixelated detector instead of single diodes, specifically an electron backscatter diffraction (EBSD) detector. We present postprocessing techniques to extract images of dislocations and surface steps, for a nitride thin film, from measurements of backscattered electron intensities and intensity distributions in unprocessed EBSD patterns. In virtual diode (VD) imaging, the backscattered electron intensity is monitored for a selected segment of the unprocessed EBSD patterns. In center of mass (COM) imaging, the position of the center of the backscattered electron intensity distribution is monitored. Additionally, both methods can be combined (VDCOM). Using both VD and VDCOM, images of only threading dislocations, or dislocations and surface steps can be produced, with VDCOM images exhibiting better signal-to-noise. The applicability of VDCOM imaging is demonstrated across a range of nitride semiconductor thin films, with varying surface step and dislocation densities.

Mediation role of anxiety on social support and depression among diabetic patients in elderly caring social organizations in China during COVID-19 pandemic: a cross-sectional study

BACKGROUND

Diabetes has become a prominent global public health problem, which is an important cause of death, disease burden, and medical and health economic burden. Previous studies have reported that majority of persons diagnosed with diabetes later presented with psychological and mental health diseases. The study aimed to explore the mediation role of anxiety on social support and depression among diabetic patents in elderly caring social organizations (SOs).

METHODS

A multi-stage stratified cluster random sampling method was used in this cross-sectional study, and a questionnaire consisting of demographic questionnaire, MSPSS, GAD-7, and CES-D-10 was utilized to gather data. SPSS 22.0 and MPLUS 7.4 were used for statistical analysis. Spearman correlation analysis was employed to investigate correlations of key variables. A generalized linear model was used to exam factors associated with depression. Finally, the mediation effect among study variables was investigated by structural equation modeling (SEM).

RESULTS

The average scores of social support, anxiety, and depression were 58.41 ± 14.67, 2.95 ± 3.95, and 7.24 ± 5.53, respectively. The factors of gender, social support, and anxiety were identified as significantly influential factors related to depression among diabetic patients in elderly caring SOs. The effect of social support on depression was significantly mediated by anxiety (β = -0.467, 95%CI: -0.813 to -0.251). Furthermore, anxiety partially mediated the relationship between family support and depression (β = -0.112, 95%CI: -0.229 to -0.012), and anxiety functioned as a complete mediator in the effect of significant others' support and depression (β = -0.135, 95%CI: -0.282 to -0.024).

CONCLUSIONS

The indirect effect of social support on depression through anxiety among diabetic patients in elderly caring SOs was elucidated. Social support played a key role in maintaining and regulating their mental health, particularly from family and significant others. Social support provided by both family and significant others exerted an important influence on maintaining and regulating their mental health. In light of this pathway, the elderly caring SOs should enhance the magnitude of social support from these two sources, thereby diminishing the likelihood of experiencing anxiety and depression.

Cell type and gene regulatory network approaches in the evolution of spiralian biomineralisation

Biomineralisation is the process by which living organisms produce hard structures such as shells and bone. There are multiple independent origins of biomineralised skeletons across the tree of life. This review gives a glimpse into the diversity of spiralian biominerals and what they can teach us about the evolution of novelty. It discusses different levels of biological organisation that may be informative to understand the evolution of biomineralisation and considers the relationship between skeletal and non-skeletal biominerals. More specifically, this review explores if cell type and gene regulatory network approaches could enhance our understanding of the evolutionary origins of biomineralisation.

Pion Detection Using Single Photon Avalanche Diodes

We present the first reported use of a CMOS-compatible single photon avalanche diode (SPAD) array for the detection of high-energy charged particles, specifically pions, using the Super Proton Synchrotron at CERN, the European Organization for Nuclear Research. The results confirm the detection of incident high-energy pions at 120 GeV, minimally ionizing, which complements the variety of ionizing radiation that can be detected with CMOS SPADs.

The association of long-term exposure to outdoor air pollution with all-cause GP visits and hospital admissions by ethnicity and country of birth in the United Kingdom

BACKGROUND

Air pollution is associated with poor health. Yet, more research is needed to reveal the association of long-term exposure to outdoor air pollution with less studied health outcomes like hospital admissions and general-practitioner (GP) visits and whether this association is stronger for ethnic minorities compared to the rest of population. This study investigates the association between air pollution and all-cause GP visits and hospital admissions by ethnicity in the United-Kingdom (UK).

METHODS

We used individual-level longitudinal data from the "UK Household Longitudinal Study" including 46,442 adult individuals who provided 140,466 responses across five years (2015-2019). This data was linked to yearly concentrations of NO2, SO2, and particulate-matter (PM10, PM2.5) outdoor pollution using the Lower Super Output Area (LSOA) of residence for each individual. Multilevel mixed-effects ordered logistic models were used to assess the association between air pollution and all-cause GP visits and hospital admissions.

RESULTS

We found higher odds of hospital admissions per 1 μg/m3 increase in annual concentrations of NO2 (OR = 1.008; 95%CI = 1.004-1.012), SO2 (OR = 1.048; 95%CI = 1.014-1.083), PM10 (OR = 1.011; 95%CI = 1.003-1.018), and PM2.5 (OR = 1.018; 95%CI = 1.007-1.029) pollutants. Higher odds of GP visits were also observed with increased exposure to NO2 (OR = 1.010; 95%CI = 1.006-1.014) and SO2 (OR = 1.114; 95%CI = 1.077-1.152) pollutants. The observed associations did not differ across ethnic groups, but by country of birth, they were more pronounced in individuals born outside UK than those born in UK.

CONCLUSION

This study supports an association between higher exposure to outdoor air pollution and increased all-cause hospital admissions and GP visits. Further longitudinal studies with longer follow-up time periods may be able to reveal more definite conclusions on the influence of ethnicity on the association between long-term outdoor air pollution and both hospital admissions and GP visits.

Improving interfacial shear strength of fique fibres using an acrylic coating

Natural fibres have proven to be a potential alternative to replace synthetic fibres in some composite materials applications. However, drawbacks such as impregnation difficulties and the poor fibre-matrix interface limit the use of natural fibres in high-performance applications. This work proposes using an acrylic resin to coat the fibre surface to enhance the interfacial compatibility among fique fibres and polyester resin. Pull-out tests revealed an improvement in the interfacial shear strength of about 110% for coated fibres. Furthermore, nanoindentation test, Micro Raman spectroscopy and scanning electronic microscopy indicated that the acrylic resin eliminates the gap at the fibre/matrix interface seen in the uncoated fibres. Observed behaviour could be attributed to a better chemical bonding between the fibre and matrix and is also hypothesised that the elastic characteristic of the coating helps to transfer loads effectively from the matrix to the fibre.

Direct Light-Enabled Access to α-Boryl Radicals: Application in the Stereodivergent Synthesis of Allyl Boronic Esters

Operationally simple strategies to assemble boron containing organic frameworks are highly enabling in organic synthesis. While conventional retrosynthetic logic has engendered many platforms focusing on the direct formation of C-B bonds, α-boryl radicals have recently reemerged as versatile open-shell alternatives to access organoborons via adjacent C-C bond formation. Direct light-enabled α-activation is currently contingent on photo- or transition metal-catalysis activation to efficiently generate radical species. Here, we disclose a facile activation of α-halo boronic esters using only visible light and a simple Lewis base to enable homolytic scission. Intermolecular addition to styrenes facilitates the rapid construction of highly versatile E-allylic boronic esters. The simplicity of activation permits the strategic merger of this construct with selective energy transfer catalysis to enable the complimentary stereodivergent synthesis of Z-allylic boronic esters.

Synchronous multi-segmental activity between metachronal waves controls locomotion speed in Drosophila larvae

The ability to adjust the speed of locomotion is essential for survival. In limbed animals, the frequency of locomotion is modulated primarily by changing the duration of the stance phase. The underlying neural mechanisms of this selective modulation remain an open question. Here, we report a neural circuit controlling a similarly selective adjustment of locomotion frequency in Drosophila larvae. Drosophila larvae crawl using peristaltic waves of muscle contractions. We find that larvae adjust the frequency of locomotion mostly by varying the time between consecutive contraction waves, reminiscent of limbed locomotion. A specific set of muscles, the lateral transverse (LT) muscles, co-contract in all segments during this phase, the duration of which sets the duration of the interwave phase. We identify two types of GABAergic interneurons in the LT neural network, premotor neuron A26f and its presynaptic partner A31c, which exhibit segmentally synchronized activity and control locomotor frequency by setting the amplitude and duration of LT muscle contractions. Altogether, our results reveal an inhibitory central circuit that sets the frequency of locomotion by controlling the duration of the period in between peristaltic waves. Further analysis of the descending inputs onto this circuit will help understand the higher control of this selective modulation.

Bayesian cluster analysis

Bayesian cluster analysis offers substantial benefits over algorithmic approaches by providing not only point estimates but also uncertainty in the clustering structure and patterns within each cluster. An overview of Bayesian cluster analysis is provided, including both model-based and loss-based approaches, along with a discussion on the importance of the kernel or loss selected and prior specification. Advantages are demonstrated in an application to cluster cells and discover latent cell types in single-cell RNA sequencing data to study embryonic cellular development. Lastly, we focus on the ongoing debate between finite and infinite mixtures in a model-based approach and robustness to model misspecification. While much of the debate and asymptotic theory focuses on the marginal posterior of the number of clusters, we empirically show that quite a different behaviour is obtained when estimating the full clustering structure. This article is part of the theme issue 'Bayesian inference: challenges, perspectives, and prospects'.

Antisolvent Additive Engineering for Boosting Performance and Stability of Graded Heterojunction Perovskite Solar Cells Using Amide-Functionalized Graphene Quantum Dots

Additive and antisolvent engineering strategies are outstandingly efficient in enhancing perovskite quality, photovoltaic performance, and stability of perovskite solar cells (PSCs). In this work, an effective approach is applied by coupling the antisolvent mixture and multi-functional additive procedures, which is recognized as antisolvent additive engineering (AAE). The graphene quantum dots functionalized with amide (AGQDs), which consists of carbonyl, amine, and long hydrophobic alkyl chain functional groups, are added to the antisolvent mixture of toluene (T) and hexane (H) as an efficient additive to form the CH₃NH₃PbI₃ (MAPI):AGQDs graded heterojunction structure. A broad range of analytical techniques, including scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, space charge limited current, UV-visible spectroscopy, external quantum efficiency, and time-of-flight secondary ion mass spectrometry, are used to investigate the effect of AAE treatment with AGQDs on the quality of perovskite film and performance of the PSCs. Importantly, not only a uniform and dense perovskite film with hydrophobic property is obtained but also defects on the perovskite surface are significantly passivated by the interaction between AGQDs and uncoordinated Pb²⁺. As a result, an enhanced power conversion efficiency (PCE) of 19.10% is achieved for the champion PSCs treated with AGQD additive, compared to the PCE of 16.00% for untreated reference PSCs. In addition, the high-efficiency PSCs based on AGQDs show high stability and maintain 89% of their initial PCE after 960 h in ambient conditions.

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences

Machine learning (ML) methodology used in the social and health sciences needs to fit the intended research purposes of description, prediction, or causal inference. This paper provides a comprehensive, systematic meta-mapping of research questions in the social and health sciences to appropriate ML approaches by incorporating the necessary requirements to statistical analysis in these disciplines. We map the established classification into description, prediction, counterfactual prediction, and causal structural learning to common research goals, such as estimating prevalence of adverse social or health outcomes, predicting the risk of an event, and identifying risk factors or causes of adverse outcomes, and explain common ML performance metrics. Such mapping may help to fully exploit the benefits of ML while considering domain-specific aspects relevant to the social and health sciences and hopefully contribute to the acceleration of the uptake of ML applications to advance both basic and applied social and health sciences research.

Evaluation of the role of KPNA2 mutations in breast cancer prognosis using bioinformatics datasets

Breast cancer, comprising of several sub-phenotypes, is a leading cause of female cancer-related mortality in the UK and accounts for 15% of all cancer cases. Chemoresistant sub phenotypes of breast cancer remain a particular challenge. However, the rapidly-growing availability of clinical datasets, presents the scope to underpin a data-driven precision medicine-based approach exploring new targets for diagnostic and therapeutic interventions.We report the application of a bioinformatics-based approach probing the expression and prognostic role of Karyopherin-2 alpha (KPNA2) in breast cancer prognosis. Aberrant KPNA2 overexpression is directly correlated with aggressive tumour phenotypes and poor patient survival outcomes. We examined the existing clinical data available on a range of commonly occurring mutations of KPNA2 and their correlation with patient survival.Our analysis of clinical gene expression datasets show that KPNA2 is frequently amplified in breast cancer, with differences in expression levels observed as a function of patient age and clinicopathologic parameters. We also found that aberrant KPNA2 overexpression is directly correlated with poor patient prognosis, warranting further investigation of KPNA2 as an actionable target for patient stratification or the design of novel chemotherapy agents.In the era of big data, the wealth of datasets available in the public domain can be used to underpin proof of concept studies evaluating the biomolecular pathways implicated in chemotherapy resistance in breast cancer.

Identifying factors contributing to social vulnerability through a deliberative Q-Sort process: an application to heat vulnerability in Taiwan

Extreme heat events are gaining ever more policy and societal attention under a warming climate. Although a breadth of expertises are required to understand drivers of vulnerability to hazards such as extreme heat, it is also acknowledged that expert assessments in group settings may be subject to biases and uneven power relations. In this Technical Note, we outline a structured deliberative process for supporting experts to work collaboratively to assess social vulnerability to a climate-related hazard, in this case extreme heat in Taiwanese cities. We argue that adapting elicitation approaches such as Q-Methodology for use in collaborative settings can help to organise expert discussion and enable dialogue and mutual learning, in a way that supports consensus-building on vulnerability assessment. Outcomes from our collaborative assessments suggest elderly people living alone, elderly people over 75, pre-existing circulatory diseases and level of participation in community decision-making may all be notable drivers of heat vulnerability in the Taiwanese context. Methodologically, we argue that collaborative sorting exercises offer a way to embed local and experiential knowledges into assessments of available evidence, but that strong facilitation and additional checks are necessary to ensure an inclusive process that reflects the diversity of perspectives involved.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11069-022-05280-4.

Back to square one: the bodily roots of conscious experiences in early life

Most theoretical and empirical discussions about the nature of consciousness are typically couched in a way that endorses a tacit adult-centric and vision-based perspective. This paper defends the idea that consciousness science may be put on a fruitful track for its next phase by examining the nature of subjective experiences through a bottom-up developmental lens. We draw attention to the intrinsic link between consciousness, experiences and experiencing subjects, which are first and foremost embodied and situated organisms essentially concerned with self-preservation within a precarious environment. Our paper suggests that in order to understand what consciousness 'is', one should first tackle the fundamental question: how do embodied experiences 'arise' from square one? We then highlight one key yet overlooked aspect of human consciousness studies, namely that the earliest and closest environment of an embodied experiencing subject is the body of another human experiencing subject. We present evidence speaking in favour of fairly sophisticated forms of early sensorimotor integration of bodily signals and self-generated actions already being established in utero. We conclude that these primitive and fundamentally relational and co-embodied roots of our early experiences may have a crucial impact on the way human beings consciously experience the self, body and the world across their lifespan.

Halogenases: a palette of emerging opportunities for synthetic biology-synthetic chemistry and C-H functionalisation

The enzymatic generation of carbon-halogen bonds is a powerful strategy used by both nature and synthetic chemists to tune the bioactivity, bioavailability and reactivity of compounds, opening up the opportunity for selective C-H functionalisation. Genes encoding halogenase enzymes have recently been shown to transcend all kingdoms of life. These enzymes install halogen atoms into aromatic and less activated aliphatic substrates, achieving selectivities that are often challenging to accomplish using synthetic methodologies. Significant advances in both halogenase discovery and engineering have provided a toolbox of enzymes, enabling the ready use of these catalysts in biotransformations, synthetic biology, and in combination with chemical catalysis to enable late stage C-H functionalisation. With a focus on substrate scope, this review outlines the mechanisms employed by the major classes of halogenases, while in parallel, it highlights key advances in the utilisation of the combination of enzymatic halogenation and chemical catalysis for C-H activation and diversification.

An experimentally informed statistical elasto-plastic mineralised collagen fibre model at the micrometre and nanometre lengthscale

Bone is an intriguingly complex material. It combines high strength, toughness and lightweight via an elaborate hierarchical structure. This structure results from a biologically driven self-assembly and self-organisation, and leads to different deformation mechanisms along the length scales. Characterising multiscale bone mechanics is fundamental to better understand these mechanisms including changes due to bone-related diseases. It also guides us in the design of new bio-inspired materials. A key-gap in understanding bone's behaviour exists for its fundamental mechanical unit, the mineralised collagen fibre, a composite of organic collagen molecules and inorganic mineral nanocrystals. Here, we report an experimentally informed statistical elasto-plastic model to explain the fibre behaviour including the nanoscale interplay and load transfer with its main mechanical components. We utilise data from synchrotron nanoscale imaging, and combined micropillar compression and synchrotron X-ray scattering to develop the model. We see that a 10-15% micro- and nanomechanical heterogeneity in mechanical properties is essential to promote the ductile microscale behaviour preventing an abrupt overall failure even when individual fibrils have failed. We see that mineral particles take up 45% of strain compared to collagen molecules while interfibrillar shearing seems to enable the ductile post-yield behaviour. Our results suggest that a change in mineralisation and fibril-to-matrix interaction leads to different mechanical properties among mineralised tissues. Our model operates at crystalline-, molecular- and continuum-levels and sheds light on the micro- and nanoscale deformation of fibril-matrix reinforced composites.

A review of combined sewer overflows as a source of wastewater-derived emerging contaminants in the environment and their management

Emerging contaminants such as pharmaceuticals, illicit drugs and personal care products can be released to the environment in untreated wastewater/stormwater mixtures following storm events. The frequency and intensity of combined sewer overflows (CSOs) has increased in some areas due to increasing urbanisation and climate change. Therefore, this review provides an up-to-date overview on CSOs as an environmental source of emerging contaminants. Other than compounds with high removal, those chiral species subject to enantioselective changes (i.e. degradation or inversion) during wastewater treatment can be effective markers of CSO discharge in the environment. A proposed framework for the selection of emerging contaminants as markers of CSOs is outlined. Studies have demonstrated that CSOs can be the main source of emerging contaminants with high removal efficiency during wastewater treatment (e.g. > 90%). However, the impact of CSOs on the environment is location specific and requires decision-making on their appropriate management at catchment level. This process would be aided by further studies on CSOs which incorporate the monitoring of emerging contaminants and their effects in the environment with those more routinely monitored pollutants (e.g. pathogens and priority substances). Mitigation and treatment strategies for emerging contaminants in CSOs are also discussed.

Complexome profile of Toxoplasma gondii mitochondria identifies divergent subunits of respiratory chain complexes including new subunits of cytochrome bc1 complex

The mitochondrial electron transport chain (mETC) and F1Fo-ATP synthase are of central importance for energy and metabolism in eukaryotic cells. The Apicomplexa, important pathogens of humans causing diseases such as toxoplasmosis and malaria, depend on their mETC in every known stage of their complicated life cycles. Here, using a complexome profiling proteomic approach, we have characterised the Toxoplasma mETC complexes and F1Fo-ATP synthase. We identified and assigned 60 proteins to complexes II, IV and F1Fo-ATP synthase of Toxoplasma, of which 16 have not been identified previously. Notably, our complexome profile elucidates the composition of the Toxoplasma complex III, the target of clinically used drugs such as atovaquone. We identified two new homologous subunits and two new parasite-specific subunits, one of which is broadly conserved in myzozoans. We demonstrate all four proteins are essential for complex III stability and parasite growth, and show their depletion leads to decreased mitochondrial potential, supporting their assignment as complex III subunits. Our study highlights the divergent subunit composition of the apicomplexan mETC and F1Fo-ATP synthase complexes and sets the stage for future structural and drug discovery studies.

From first concepts to Diasonograph: The role of product design in the first medical obstetric ultrasound machines in 1960s Glasgow

In the late 1950s and early-to-mid-1960s, Glasgow led the world in the development of diagnostic obstetric ultrasound technology, the result of fortuitous collaboration between key individuals advancing the application of an industrial technology. Originally used to detect flaws in metal pressure vessels, the obstetrician Ian Donald, during his military service, reflected on how ultrasound could benefit his own field. Donald involved the engineer Tom Brown to tackle the technical challenges. Brown, in turn, employed a young graduating industrial designer, Dugald Cameron, to address the design, aesthetic and ergonomic aspects of these early engineering prototypes. While previous accounts of these developments have rightly celebrated the medical, technical engineering and imaging achievements of this innovative technology, the discussion of the role of the creative design expertise which addressed serious ergonomic, aesthetic and production manufacturing shortcomings of the first prototypes has been less coherent. This article relates, through key drawings, extracts from witness statements and discussions with Cameron himself, the key design decisions and features resulting in the Sundén and Diasonograph machines, the latter being the world's first commercial production-series obstetric ultrasound machine, deployed in Glasgow hospitals and beyond.

Structure-based Hamiltonian model for IsiA uncovers a highly robust pigment-protein complex

The iron stress-induced protein A (IsiA) is a source of interest and debate in biological research. The IsiA supercomplex, binding over 200 chlorophylls, assembles in multimeric rings around photosystem I (PSI). Recently, the IsiA-PSI structure from Synechocystis sp. PCC 6803 was resolved to 3.48 Å. Based on this structure, we created a model simulating a single excitation event in an IsiA monomer. This model enabled us to calculate the fluorescence and the localization of the excitation in the IsiA structure. To further examine this system, noise was introduced to the model in two forms-thermal and positional. Introducing noise highlights the functional differences in the system between cryogenic temperatures and biologically relevant temperatures. Our results show that the energetics of the IsiA pigment-protein complex are very robust at room temperature. Nevertheless, shifts in the position of specific chlorophylls lead to large changes in their optical and fluorescence properties. Based on these results, we discuss the implication of highly robust structures, with potential for serving different roles in a context-dependent manner, on our understanding of the function and evolution of photosynthetic processes.

Phenotypic delay in the evolution of bacterial antibiotic resistance: Mechanistic models and their implications

Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.

Ultradeep Microbial Communities at 4.4 km within Crystalline Bedrock: Implications for Habitability in a Planetary Context

The deep bedrock surroundings are an analog for extraterrestrial habitats for life. In this study, we investigated microbial life within anoxic ultradeep boreholes in Precambrian bedrock, including the adaptation to environmental conditions and lifestyle of these organisms. Samples were collected from Pyhäsalmi mine environment in central Finland and from geothermal drilling wells in Otaniemi, Espoo, in southern Finland. Microbial communities inhabiting the up to 4.4 km deep bedrock were characterized with phylogenetic marker gene (16S rRNA genes and fungal ITS region) amplicon and DNA and cDNA metagenomic sequencing. Functional marker genes (dsrB, mcrA, narG) were quantified with qPCR. Results showed that although crystalline bedrock provides very limited substrates for life, the microbial communities are diverse. Gammaproteobacterial phylotypes were most dominant in both studied sites. Alkanindiges -affiliating OTU was dominating in Pyhäsalmi fluids, while different depths of Otaniemi samples were dominated by Pseudomonas. One of the most common OTUs detected from Otaniemi could only be classified to phylum level, highlighting the uncharacterized nature of the deep biosphere in bedrock. Chemoheterotrophy, fermentation and nitrogen cycling are potentially significant metabolisms in these ultradeep environments. To conclude, this study provides information on microbial ecology of low biomass, carbon-depleted and energy-deprived deep subsurface environment. This information is useful in the prospect of finding life in other planetary bodies.

Cardiomyocyte mechanodynamics under conditions of actin remodelling

The mechanical performance of cardiomyocytes (CMs) is an important indicator of their maturation state and of primary importance for the development of therapies based on cardiac stem cells. As the mechanical analysis of adherent cells at high-throughput remains challenging, we explore the applicability of real-time deformability cytometry (RT-DC) to probe cardiomyocytes in suspension. RT-DC is a microfluidic technology allowing for real-time mechanical analysis of thousands of cells with a throughput exceeding 1000 cells per second. For CMs derived from human-induced pluripotent stem cells, we determined a Young's modulus of 1.25 ± 0.08 kPa which is in close range to previous reports. Upon challenging the cytoskeleton with cytochalasin D (CytoD) to induce filamentous actin depolymerization, we distinguish three different regimes in cellular elasticity. Transitions are observed below 10 nM and above 103 nM and are characterized by a decrease in Young's modulus. These regimes can be linked to cytoskeletal and sarcomeric actin contributions by CM contractility measurements at varying CytoD concentrations, where we observe a significant reduction in pulse duration only above 103 nM while no change is found for compound exposure at lower concentrations. Comparing our results to mechanical cell measurements using atomic force microscopy, we demonstrate for the first time to our knowledge, the feasibility of using a microfluidic technique to measure mechanical properties of large samples of adherent cells while linking our results to the composition of the cytoskeletal network. This article is part of a discussion meeting issue 'Single cell ecology'.

Interaction between row-type genes in barley controls meristem determinacy and reveals novel routes to improved grain

Hordeum species develop a central spikelet flanked by two lateral spikelets at each inflorescence node. In 'two-rowed' spikes, the central spikelet alone is fertile and sets grain, while in 'six-rowed' spikes, lateral spikelets can also produce grain. Induced loss-of-function alleles of any of five Six-rowed spike (VRS) genes (VRS1-5) cause complete to intermediate gains of lateral spikelet fertility. Current six-row cultivars contain natural defective vrs1 and vrs5 alleles. Little information is known about VRS mechanism(s). We used comparative developmental, expression and genetic analyses on single and double vrs mutants to learn more about how VRS genes control development and assess their agronomic potential. We show that all VRS genes repress fertility at carpel and awn emergence in developing lateral spikelets. VRS4, VRS3 and VRS5 work through VRS1 to suppress fertility, probably by inducing VRS1 expression. Pairing vrs3, vrs4 or vrs5 alleles increased lateral spikelet fertility, despite the presence of a functional VRS1 allele. The vrs3 allele caused loss of spikelet identity and determinacy, improved grain homogeneity and increased tillering in a vrs4 background, while with vrs5, decreased tiller number and increased grain weight. Interactions amongst VRS genes control spikelet infertility, determinacy and outgrowth, and novel routes to improving six-row grain.

Attosecond-resolution Hong-Ou-Mandel interferometry

When two indistinguishable photons are each incident on separate input ports of a beamsplitter, they "bunch" deterministically, exiting via the same port as a direct consequence of their bosonic nature. This two-photon interference effect has long-held the potential for application in precision measurement of time delays, such as those induced by transparent specimens with unknown thickness profiles. However, the technique has never achieved resolutions significantly better than the few-femtosecond (micrometer) scale other than in a common-path geometry that severely limits applications. We develop the precision of Hong-Ou-Mandel interferometry toward the ultimate limits dictated by statistical estimation theory, achieving few-attosecond (or nanometer path length) scale resolutions in a dual-arm geometry, thus providing access to length scales pertinent to cell biology and monoatomic layer two-dimensional materials.

Two essential Thioredoxins mediate apicoplast biogenesis, protein import, and gene expression in Toxoplasma gondii

Apicomplexan parasites are global killers, being the causative agents of diseases like toxoplasmosis and malaria. These parasites are known to be hypersensitive to redox imbalance, yet little is understood about the cellular roles of their various redox regulators. The apicoplast, an essential plastid organelle, is a verified apicomplexan drug target. Nuclear-encoded apicoplast proteins traffic through the ER and multiple apicoplast sub-compartments to their place of function. We propose that thioredoxins contribute to the control of protein trafficking and of protein function within these apicoplast compartments. We studied the role of two Toxoplasma gondiiapicoplast thioredoxins (TgATrx), both essential for parasite survival. By describing the cellular phenotypes of the conditional depletion of either of these redox regulated enzymes we show that each of them contributes to a different apicoplast biogenesis pathway. We provide evidence for TgATrx1’s involvement in ER to apicoplast trafficking and TgATrx2 in the control of apicoplast gene expression components. Substrate pull-down further recognizes gene expression factors that interact with TgATrx2. We use genetic complementation to demonstrate that the function of both TgATrxs is dependent on their disulphide exchange activity. Finally, TgATrx2 is divergent from human thioredoxins. We demonstrate its activity in vitro thus providing scope for drug screening. Our study represents the first functional characterization of thioredoxins in Toxoplasma, highlights the importance of redox regulation of apicoplast functions and provides new tools to study redox biology in these parasites.

To survive, apicomplexan parasites must adjust to the redox insults they experience. These parasites undergo redox stresses induced by the host cell within which they live, by the host immune system, and by their own metabolic activities. Yet the myriad of cellular processes that are affected by redox changes and that may take part in maintaining the redox balance within the parasite are largely understudied. Thioredoxins are enzymes that link the redox state of subcellular environments to the functional state or the cellular trafficking of their substrate proteins. In this work, we identify two pathways that are controlled by two thioredoxins in the apicomplexan Toxoplasma gondii, and demonstrate that both are essential for parasite survival. We show that each of these enzymes contributes to the function of the apicomplexan plastid, the apicoplast, a unique parasite organelle with importance for drug discovery efforts. We thus highlight that part of the apicomplexan sensitivity to redox imbalance is specifically related to the apicoplast, and point at the importance of thioredoxins in mediating apicoplast biogenesis. Finally, our work raises the potential of apicoplast thioredoxins as new drug targets.

Seasonal Regulation of Petal Number

Four petals characterize the flowers of most species in the Brassicaceae family, and this phenotype is generally robust to genetic and environmental variation. A variable petal number distinguishes the flowers of Cardamine hirsuta from those of its close relative Arabidopsis (Arabidopsis thaliana), and allelic variation at many loci contribute to this trait. However, it is less clear whether C. hirsuta petal number varies in response to seasonal changes in environment. To address this question, we assessed whether petal number responds to a suite of environmental and endogenous cues that regulate flowering time in C. hirsuta We found that petal number showed seasonal variation in C. hirsuta, such that spring flowering plants developed more petals than those flowering in summer. Conditions associated with spring flowering, including cool ambient temperature, short photoperiod, and vernalization, all increased petal number in C. hirsuta Cool temperature caused the strongest increase in petal number and lengthened the time interval over which floral meristems matured. We performed live imaging of early flower development and showed that floral buds developed more slowly at 15°C versus 20°C. This extended phase of floral meristem formation, coupled with slower growth of sepals at 15°C, produced larger intersepal regions with more space available for petal initiation. In summary, the growth and maturation of floral buds is associated with variable petal number in C. hirsuta and responds to seasonal changes in ambient temperature.

Beyond the Hypercube: Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational Networks

Evolutionary pathways describe trajectories of biological evolution in the space of different variants of organisms (genotypes). The probability of existence and the number of evolutionary pathways that lead from a given genotype to a better-adapted genotype are important measures of accessibility of local fitness optima and the reproducibility of evolution. Both quantities have been studied in simple mathematical models where genotypes are represented as binary sequences of two types of basic units, and the network of permitted mutations between the genotypes is a hypercube graph. However, it is unclear how these results translate to the biologically relevant case in which genotypes are represented by sequences of more than two units, for example four nucleotides (DNA) or 20 amino acids (proteins), and the mutational graph is not the hypercube. Here we investigate accessibility of the best-adapted genotype in the general case of K > 2 units. Using computer generated and experimental fitness landscapes we show that accessibility of the global fitness maximum increases with K and can be much higher than for binary sequences. The increase in accessibility comes from the increase in the number of indirect trajectories exploited by evolution for higher K. As one of the consequences, the fraction of genotypes that are accessible increases by three orders of magnitude when the number of units K increases from 2 to 16 for landscapes of size N ∼ 10⁶ genotypes. This suggests that evolution can follow many different trajectories on such landscapes and the reconstruction of evolutionary pathways from experimental data might be an extremely difficult task.

Biological evolution is driven by heritable, genetic alterations that affect the fitness of organisms. However, the pool of “fitter” variants (genotypes) is often restricted and it is not at all obvious how evolution finds its way from low-fitness to high-fitness genotypes in a complex, multidimensional “fitness landscapes” with many peaks (fit organisms) and valleys (unfit ones). To address this question we investigate how likely it is for biological evolution to find a way “uphill” from a lower-fitness organism to the best adapted organism. We discover that the accessibility of the fittest organism depends on the number of types of basic “units” used to encode genotypes. These units can be, for example, the four DNA nucleotides A,T,C,G, or the ∼20 amino acids used for synthesizing proteins, and the choice of the most appropriate unit is dictated by how the genotypes and the fitnesses are related—a relationship that researchers have begun to unveil only recently. We find that increasing the number of units strongly increases the probability that there will be at least one uphill path to the best-adapted genotype, and the number of evolutionary pathways leading to it. Our findings suggest that biological evolution can follow many more pathways than previously thought.

Design and fabrication of diffractive atom chips for laser cooling and trapping

It has recently been shown that optical reflection gratings fabricated directly into an atom chip provide a simple and effective way to trap and cool substantial clouds of atoms (Nshii et al. in Nat Nanotechnol 8:321-324, 2013; McGilligan et al. in Opt Express 23(7):8948-8959, 2015). In this article, we describe how the gratings are designed and microfabricated and we characterise their optical properties, which determine their effectiveness as a cold atom source. We use simple scalar diffraction theory to understand how the morphology of the gratings determines the power in the diffracted beams.