29 research outputs found
Improving the Thermal Stability of Cellobiohydrolase Cel7A from \u3cem\u3eHypocrea jecorina\u3c/em\u3e by Directed Evolution
Secreted mixtures of Hypocrea jecorina cellulases are able to efficiently degrade cellulosic biomass to fermentable sugars at large, commercially relevant scales. H. jecorina Cel7A, cellobiohydrolase I, from glycoside hydrolase family 7, is the workhorse enzyme of the process. However, the thermal stability of Cel7A limits its use to processes where temperatures are no higher than 50 °C. Enhanced thermal stability is desirable to enable the use of higher processing temperatures and to improve the economic feasibility of industrial biomass conversion. Here, we enhanced the thermal stability of Cel7A through directed evolution. Sites with increased thermal stability properties were combined, and a Cel7A variant (FCA398) was obtained, which exhibited a 10.4 °C increase in Tm and a 44-fold greater half-life compared with the wild-type enzyme. This Cel7A variant contains 18 mutated sites and is active under application conditions up to at least 75 °C. The X-ray crystal structure of the catalytic domain was determined at 2.1 Ă
resolution and showed that the effects of the mutations are local and do not introduce major backbone conformational changes. Molecular dynamics simulations revealed that the catalytic domain of wild-type Cel7A and the FCA398 variant exhibit similar behavior at 300 K, whereas at elevated temperature (475 and 525 K), the FCA398 variant fluctuates less and maintains more native contacts over time. Combining the structural and dynamic investigations, rationales were developed for the stabilizing effect at many of the mutated sites
Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities:A multicenter study in 3132 memory clinic patients
INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ¹ 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and AĂ42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and AĂ42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and AĂ42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and AĂ42 pathology affect the brain's white matter. Highlights: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.</p
Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients
INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ¹ 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and AĂ42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and AĂ42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and AĂ42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and AĂ42 pathology affect the brain's white matter. HIGHLIGHTS: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns
Change in CSF marker classification according to cut-offs.
<p>Results are CSF levels only for subjects in which reanalysis let to a different biomarker classification using the cut-offs from Amsterdam to define abnormal CSF values. On the left (A) are changes in biomarker levels for intralaboratory reanalysis and on the right (B) for interlaboratory reanalysis. The arrow represents the applied Amsterdam CSF cut-off. Analysis 1 is routine practice and analysis 2 is performed as part of the LeARN study. CSFâ=âcerebrospinal fluid, Aβâ=âamyloid beta, t-tauâ=âtotal tau, p-tauâ=âphosphorylated tau.</p
Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities:A multicenter study in 3132 memory clinic patients
INTRODUCTION: White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS: Individual patient data (n = 3,132; mean age 71.5 ¹ 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and AĂ42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.RESULTS: VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and AĂ42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION: Vascular risk factors and AĂ42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and AĂ42 pathology affect the brain's white matter. Highlights: Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.</p
Internal control data of the Amsterdam laboratory.
<p>Results are changes in high and low CSF biomarker levels for intralaboratory reanalysis in two lots (routine lot and LeARN lot) as part of internal control of data at the Amsterdam laboratory. A) Aβ1-42: Lot 1 used from February 2010 to February 2011 (nâ=â18) and lot 2 used from March to October 2012 (nâ=â17). B) T-tau: Lot 1 used from February 2010 to April 2011 (nâ=â24) and lot 2 used from March to June 2012 (nâ=â11). C) P-tau: Lot 1 used from February 2010 to April 2011 (nâ=â23) and lot 2 used from March to October 2012 (nâ=â11). CSFâ=âcerebrospinal fluid, Aβâ=âamyloid beta, t-tauâ=âtotal tau, p-tauâ=âphosphorylated tau. *P<0.001 for differences between lot of analysis 1 (routine lot) and lot of analysis 2 (LeARN lot).</p
Intralaboratory lot-to-lot variation.
<p>Results in this graph are based on deming regression and show the CSF levels of lot 1 and lot 3 for Aβ1-42 (A), t-tau (B), and p-tau (C). The slope is different for Aβ1-42 levels between lot 1 and lot 3. The mean difference in CSF levels between lot 1 and 3 was significantly different for Aβ1-42 and t-tau. Lot 1â=âclinical routine lot, lot 3â=âLeARN lot, Aβâ=âamyloid beta, t-tauâ=âtotal tau, p-tauâ=âphosphorylated tau.</p