Phenotypic Consequences Resulting from a Methionine-to-Valine Substitution at Position 48 in the HPr Protein of Streptococcus salivarius

In gram-positive bacteria, the HPr protein of the phosphoenolpyruvate:sugar phosphotransferase system (PTS) can be phosphorylated on a histidine residue at position 15 (His(15)) by enzyme I (EI) of the PTS and on a serine residue at position 46 (Ser(46)) by an ATP-dependent protein kinase (His∼P and Ser-P, respectively). We have isolated from Streptococcus salivarius ATCC 25975, by independent selection from separate cultures, two spontaneous mutants (Ga3.78 and Ga3.14) that possess a missense mutation in ptsH (the gene encoding HPr) replacing the methionine at position 48 by a valine. The mutation did not prevent the phosphorylation of HPr at His(15) by EI nor the phosphorylation at Ser(46) by the ATP-dependent HPr kinase. The levels of HPr(Ser-P) in glucose-grown cells of the parental and mutant Ga3.78 were virtually the same. However, mutant cells growing on glucose produced two- to threefold less HPr(Ser-P)(His∼P) than the wild-type strain, while the levels of free HPr and HPr(His∼P) were increased 18- and 3-fold, respectively. The mutants grew as well as the wild-type strain on PTS sugars (glucose, fructose, and mannose) and on the non-PTS sugars lactose and melibiose. However, the growth rate of both mutants on galactose, also a non-PTS sugar, decreased rapidly with time. The M48V substitution had only a minor effect on the repression of α-galactosidase, β-galactosidase, and galactokinase by glucose, but this mutation abolished diauxie by rendering cells unable to prevent the catabolism of a non-PTS sugar (lactose, galactose, and melibiose) when glucose was available. The results suggested that the capacity of the wild-type cells to preferentially metabolize glucose over non-PTS sugars resulted mainly from inhibition of the catabolism of these secondary energy sources via a HPr-dependent mechanism. This mechanism was activated following glucose but not lactose metabolism, and it did not involve HPr(Ser-P) as the only regulatory molecule

Test-retest resting-state fMRI in healthy elderly persons with a family history of Alzheimer’s disease

We present a test-retest dataset of resting-state fMRI data obtained in 80 cognitively normal elderly volunteers enrolled in the “Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease” (PREVENT-AD) Cohort. Subjects with a family history of Alzheimer's disease in first-degree relatives were recruited as part of an on-going double blind randomized clinical trial of Naproxen or placebo. Two pairs of scans were acquired ~3 months apart, allowing the assessment of both intra- and inter-session reliability, with the possible caveat of treatment effects as a source of inter-session variation. Using the NeuroImaging Analysis Kit (NIAK), we report on the standard quality of co-registration and motion parameters of the data, and assess their validity based on the spatial distribution of seed-based connectivity maps as well as intra- and inter-session reliability metrics in the default-mode network. This resource, released publicly as sample UM1 of the Consortium for Reliability and Reproducibility (CoRR), will benefit future studies focusing on the preclinical period preceding the appearance of dementia in Alzheimer's disease

The neurophysiological brain-fingerprint of Parkinson’s diseaseResearch in context

Summary: Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson’s disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson’s disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson’s brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson’s symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson’s brain-fingerprint aligns with that of neurotransmitter systems affected by the disease’s pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson’s disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson’s disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311)