Automated High-Definition MRI Processing Routine Robustly Detects Longitudinal Morphometry Changes in Alzheimer's Disease Patients

Longitudinal MRI studies are of increasing importance to document the time course of neurodegenerative diseases as well as neuroprotective effects of a drug candidate in clinical trials. However, manual longitudinal image assessments are time consuming and conventional assessment routines often deliver unsatisfying study outcomes. Here, we propose a profound analysis pipeline that consists of the following coordinated steps: (1) an automated and highly precise image processing stream including voxel and surface based morphometry using latest highly detailed brain atlases such as the HCP MMP 1.0 atlas with 360 cortical ROIs; (2) a profound statistical assessment using a multiplicative model of annual percent change (APC); and (3) a multiple testing correction adopted from genome-wide association studies that is optimally suited for longitudinal neuroimaging studies. We tested this analysis pipeline with 25 Alzheimer's disease patients against 25 age-matched cognitively normal subjects with a baseline and a 1-year follow-up conventional MRI scan from the ADNI-3 study. Even in this small cohort, we were able to report 22 significant measurements after multiple testing correction from SBM (including cortical volume, area and thickness) complementing only three statistically significant volume changes (left/right hippocampus and left amygdala) found by VBM. A 1-year decrease in brain morphometry coincided with an increasing clinical disability and cognitive decline in patients measured by MMSE, CDR GLOBAL, FAQ TOTAL and NPI TOTAL scores. This work shows that highly precise image assessments, APC computation and an adequate multiple testing correction can produce a significant study outcome even for small study sizes. With this, automated MRI processing is now available and reliable for routine use and clinical trials.

Interspecific and intraspecific phenotypic diversity for drought adaptation in bioenergy Arundo species

Biomass crops are commonly grown in low-grade land and selection of drought-tolerant accessions is of major importance to sustain productivity. In this work, we assess phenotypic variation under different environmental scenarios in a series of accessions of Arundo donax, and contrast it with two closely related species, Arundo donaciformis and Arundo plinii. Gas-exchange and stomatal anatomy analysis showed an elevated photosynthetic capacity in A. plinii compared to A. donax and A. donaciformis with a significant intraspecific variation in A. donax. The three species showed significantly contrasting behaviour of transpiration under developing water stress and increasing vapour pressure deficit (VPD), with A. donax being the most conservative while A. plinii showed an elevated degree of insensitivity to environmental cues. Under optimal conditions, A. donax had the highest estimated leaf area (projected leaf area) and plant dry weight although a significant reduction under water stress was observed for A. donax and A. donaciformis accessions while no differences were recorded for A. plinii between optimal growing conditions (well-watered [WW]) and reduced soil water availability (water-stressed [WS]). A. donax displayed a markedly conservative water use behaviour but elevated sensitivity of biomass accumulation under stress conditions. By contrast, in A. plinii, biomass and transpiration were largely insensitive to WS and increasing VPD, though biomass dry weight under optimal conditions was significantly lower than A. donax. We provide evidence of interspecific phenotypic variation within the Arundo genus while the intraspecific phenotypic plasticity may be exploited for further selection of superior clones under disadvantageous environmental conditions. The extensive trade-off between water use and biomass accumulation present in the three species under stress conditions provides a series of novel traits to be exploited in the selection of superior clones adapted to different environmental scenarios. Non-destructive approaches are provided to screen large populations for water-stress-tolerant A. donax clones.

Pigmentation Chemistry and Radical-Based Collagen Degradation in Alkaptonuria and Osteoarthritic Cartilage

Alkaptonuria (AKU) is a rare disease characterized by high levels of homogentisic acid (HGA); patients suffer from tissue ochronosis: dark brown pigmentation, especially of joint cartilage, leading to severe early osteoarthropathy. No molecular mechanism links elevated HGA to ochronosis; the pigment's chemical identity is still not known, nor how it induces joint cartilage degradation. Here we give key insight on HGA-derived pigment composition and collagen disruption in AKU cartilage. Synthetic pigment and pigmented human cartilage tissue both showed hydroquinone-resembling NMR signals. EPR spectroscopy showed that the synthetic pigment contains radicals. Moreover, we observed intrastrand disruption of collagen triple helix in pigmented AKU human cartilage, and in cartilage from patients with osteoarthritis. We propose that collagen degradation can occur via transient glycyl radicals, the formation of which is enhanced in AKU due to the redox environment generated by pigmentation.

Targeting proline in (phospho)proteomics

Mass spectrometry-based proteomics experiments typically start with the digestion of proteins using trypsin, chosen because of its high specificity, availability, and ease of use. It has become apparent that the sole use of trypsin may impose certain limits on our ability to grasp the full proteome, missing out particular sites of post-translational modifications, protein segments, or even subsets of proteins. To tackle this problem, alternative proteases have been introduced and shown to lead to an increase in the detectable (phospho)proteome. Here, we argue that there may be further room for improvement and explore the protease EndoPro. For optimal peptide identification rates, we explored multiple peptide fragmentation techniques (HCD, ETD, and EThcD) and employed Byonic as search algorithm. We obtain peptide IDs for about 40% of the MS2 spectra (66% for trypsin). EndoPro cleaves with high specificity at the C-terminal site of Pro and Ala residues and displays activity in a broad pH range, where we focused on its performance at pH = 2 and 5.5. The proteome coverage of EndoPro at these two pH values is rather distinct, and also complementary to the coverage obtained with trypsin. As about 40% of mammalian protein phosphorylations are proline-directed, we also explored the performance of EndoPro in phosphoproteomics. EndoPro extends the coverable phosphoproteome substantially, whereby both the, at pH = 2 and 5.5, acquired phosphoproteomes are complementary to each other and to the phosphoproteome obtained using trypsin. Hence, EndoPro is a powerful tool to exploit in (phospho)proteomics applications.