Expanding the set of rhodococcal Baeyer–Villiger monooxygenases by high-throughput cloning, expression and substrate screening

To expand the available set of Baeyer–Villiger monooxygenases (BVMOs), we have created expression constructs for producing 22 Type I BVMOs that are present in the genome of Rhodococcus jostii RHA1. Each BVMO has been probed with a large panel of potential substrates. Except for testing their substrate acceptance, also the enantioselectivity of some selected BVMOs was studied. The results provide insight into the biocatalytic potential of this collection of BVMOs and expand the biocatalytic repertoire known for BVMOs. This study also sheds light on the catalytic capacity of this large set of BVMOs that is present in this specific actinomycete. Furthermore, a comparative sequence analysis revealed a new BVMO-typifying sequence motif. This motif represents a useful tool for effective future genome mining efforts.

Structural and regulatory diversity shape HLA-C protein expression levels

Expression of HLA-C varies widely across individuals in an allele-specific manner. This variation in expression can influence efficacy of the immune response, as shown for infectious and autoimmune diseases. MicroRNA binding partially influences differential HLA-C expression, but the additional contributing factors have remained undetermined. Here we use functional and structural analyses to demonstrate that HLA-C expression is modulated not just at the RNA level, but also at the protein level. Specifically, we show that variation in exons 2 and 3, which encode the α1/α2 domains, drives differential expression of HLA-C allomorphs at the cell surface by influencing the structure of the peptide-binding cleft and the diversity of peptides bound by the HLA-C molecules. Together with a phylogenetic analysis, these results highlight the diversity and long-term balancing selection of regulatory factors that modulate HLA-C expression

Identification of diagnostic serum protein profiles of glioblastoma patients

Diagnosis of a glioblastoma (GBM) is triggered by the onset of symptoms and is based on cerebral imaging and histological examination. Serum-based biomarkers may support detection of GBM. Here, we explored serum protein concentrations of GBM patients and used data mining to explore profiles of biomarkers and determine whether these are associated with the clinical status of the patients. Gene and protein expression data for astrocytoma and GBM were used to identify secreted proteins differently expressed in tumors and in normal brain tissues. Tumor expression and serum concentrations of 14 candidate proteins were analyzed for 23 GBM patients and nine healthy subjects. Data-mining methods involving all 14 proteins were used as an initial evaluation step to find clinically informative profiles. Data mining identified a serum protein profile formed by BMP2, HSP70, and CXCL10 that enabled correct assignment to the GBM group with specificity and sensitivity of 89 and 96%, respectively (p < 0.0001, Fischer’s exact test). Survival for more than 15 months after tumor resection was associated with a profile formed by TSP1, HSP70, and IGFBP3, enabling correct assignment in all cases (p < 0.0001, Fischer’s exact test). No correlation was found with tumor size or age of the patient. This study shows that robust serum profiles for GBM may be identified by data mining on the basis of a relatively small study cohort. Profiles of more than one biomarker enable more specific assignment to the GBM and survival group than those based on single proteins, confirming earlier attempts to correlate single markers with cancer. These conceptual findings will be a basis for validation in a larger sample size

At the Biological Modeling and Simulation Frontier

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine

Cholinergic receptor pathways involved in apoptosis, cell proliferation and neuronal differentiation

Acetylcholine (ACh) has been shown to modulate neuronal differentiation during early development. Both muscarinic and nicotinic acetylcholine receptors (AChRs) regulate a wide variety of physiological responses, including apoptosis, cellular proliferation and neuronal differentiation. However, the intracellular mechanisms underlying these effects of AChR signaling are not fully understood. It is known that activation of AChRs increase cellular proliferation and neurogenesis and that regulation of intracellular calcium through AChRs may underlie the many functions of ACh. Intriguingly, activation of diverse signaling molecules such as Ras-mitogen-activated protein kinase, phosphatidylinositol 3-kinase-Akt, protein kinase C and c-Src is modulated by AChRs. Here we discuss the roles of ACh in neuronal differentiation, cell proliferation and apoptosis. We also discuss the pathways involved in these processes, as well as the effects of novel endogenous AChRs agonists and strategies to enhance neuronal-differentiation of stem and neural progenitor cells. Further understanding of the intracellular mechanisms underlying AChR signaling may provide insights for novel therapeutic strategies, as abnormal AChR activity is present in many diseases

Measurement of the electron reconstruction efficiency at LHCb

The single electron track-reconstruction efficiency is calibrated using a sample corresponding to 1.3 fb−1 of pp collision data recorded with the LHCb detector in 2017. This measurement exploits B+→ J/ψ(e+e−)K+ decays, where one of the electrons is fully reconstructed and paired with the kaon, while the other electron is reconstructed using only the information of the vertex detector. Despite this partial reconstruction, kinematic and geometric constraints allow the B meson mass to be reconstructed and the signal to be well separated from backgrounds. This in turn allows the electron reconstruction efficiency to be measured by matching the partial track segment found in the vertex detector to tracks found by LHCb's regular reconstruction algorithms. The agreement between data and simulation is evaluated, and corrections are derived for simulated electrons in bins of kinematics. These correction factors allow LHCb to measure branching fractions involving single electrons with a systematic uncertainty below 1%

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021

Precise determination of the B-s(0)-B-s(-0) oscillation frequency

Mesons comprising a beauty quark and a strange quark can oscillate between particle (B0s) and antiparticle (B0s) flavour eigenstates, with a frequency given by the mass difference between heavy and light mass eigenstates, deltams. Here we present ameasurement of deltams using B0s2DsPi decays produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The oscillation frequency is found to be deltams = 17.7683 +- 0.0051 +- 0.0032 ps-1, where the first uncertainty is statistical and the second systematic. This measurement improves upon the current deltams precision by a factor of two. We combine this result with previous LHCb measurements to determine deltams = 17.7656 +- 0.0057 ps-1, which is the legacy measurement of the original LHCb detector.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2021-005.html (LHCb public pages

Study of the ψ2(3823)ψ_2(3823) and χc1(3872)χ_{c1}(3872) states in B+→(Jψπ+π−)K+B^+ \rightarrow \left( Jψπ^+π^-\right)K^+ decays

The decays $B^+\rightarrow J/\psi \pi^+ \pi^- K^+$ are studied using a data set corresponding to an integrated luminosity of 9fb$^{-1}$ collected with the LHCb detector in proton-proton collisions between 2011 and 2018. Precise measurements of the ratios of branching fractions with the intermediate $\psi_2(3823)$, $\chi_{c1}(3872)$ and $\psi(2S)$ states are reported. The decay of $B^+\rightarrow \psi_2(3823)K^+$ with $\psi_2(3823)\rightarrow J\psi\pi^+\pi^-$ is observed for the first time with a significance of 5.1 standard deviations. The mass differences between the $\psi_2(3823)$, $\chi_{c1}(3872)$ and $\psi(2S)$ states are measured to be $$\begin{array}{rcl} m_{\chi_{c1(3872)}} - m_{\psi_2(3823)} &= & 47.50 \pm 0.53 \pm 0.13\,\mathrm{MeV/}c^2\,, \\ m_{\psi_2(3823)} - m_{\psi(2S)} &= & 137.98 \pm 0.53 \pm 0.14\,\mathrm{MeV/}c^2\,, \\ m_{\chi_{c1}(3872)} - m_{\psi(2S)} &= & 185.49 \pm 0.06 \pm 0.03\,\mathrm{MeV/}c^2\,, \end{array}$$ resulting in the most precise determination of the $\chi_{c1}(3782)$ mass. The width of the $\psi_2(3823)$ state is found to be below 5.2MeV at 90\% confidence level. The Breit-Wigner width of the $\chi_{c1}(3872)$ state is measured to be $$\Gamma^{\mathrm{BW}}_{\chi_{c1}(3872)} = 0.96^{+0.19}_{-0.18}\pm0.21 \mathrm{MeV},$$ which is inconsistent with zero by 5.5 standard deviations