Microbial resource allocation for phosphatase synthesis reflects the availability of inorganic phosphorus across various soils

According to the resource allocation model for extracellular enzyme synthesis, microorganisms should preferentially allocate their resources to phosphorus (P)-acquiring enzyme synthesis when P availability is low in soils. However, the validity of this model across different soil types and soils differing in their microbial community composition has not been well demonstrated. Here we investigated whether the resource allocation model for phosphatase synthesis is applicable across different soil types (Andosols, Acrisols, Cambisols, and Fluvisols) and land uses (arable and forest), and we examined which soil test P and/or P fraction microorganisms responded to when investing their resources in phosphatase synthesis in the soils. The ratio of alkaline phosphatase (ALP) to β-d-glucosidase (BG) activities in the arable soils and the ratio of acid phosphatase (ACP) to BG activities in the forest soils were significantly negatively related with the available inorganic P concentration. We also observed significant effects of available inorganic P, pH, soil types, and land uses on the (ACP + ALP)/BG ratio when the data for the arable and forest soils were combined and used in a stepwise multiple regression analysis. These results suggest that microbial resource allocation for phosphatase synthesis is primarily controlled by available inorganic P concentration and soil pH, but the effects of soil types and land uses are also significant.     

Pressurized Pepsin Digestion in Proteomics: AN AUTOMATABLE ALTERNATIVE TO TRYPSIN FOR INTEGRATED TOP-DOWN BOTTOM-UP PROTEOMICS*

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome.In-depth characterization and quantitation of protein isoforms, including post-translationally modified proteins, are challenging goals of contemporary proteomics. Traditionally, top-down (1, 2) and bottom-up (3, 4) proteomics have been two distinct analytical paths for liquid-based proteomics analysis. Top-down proteomics is the mass spectrometry (MS)-based characterization of intact proteins, whereas bottom-up proteomics requires a chemical or enzymatic proteolytic digestion of all proteins into peptides prior to MS analysis. Both strategies have their own strengths and challenges and can be thought of as complementary rather than competing analytical techniques.In a top-down proteomics approach, proteins are usually separated by one- or two-dimensional liquid chromatography (LC) and identified using high performance MS (5, 6). This approach is very attractive because it allows the identification of protein isoforms arising from various amino acid modifications, genetic variants (e.g. single nucleotide polymorphisms), mRNA splice variants, and multisite modifications (7) (e.g. specific histone modifications) as well as characterization of proteolytic processing events. However, there are several challenges that have limited the broad application of the approach. Typically, intact proteins are less soluble than their peptide complement, which effectively results in greater losses during various stages of sample handling (i.e. limited sensitivity). Similarly, proteins above ∼40–50 kDa in size are more difficult to ionize, detect, and dissociate in most high throughput MS work flows. Additionally, major challenges associated with MS data interpretation and sensitivity, especially for higher molecular mass proteins (>100 kDa) and highly hydrophobic proteins (e.g. integral membrane proteins), remain largely unsolved, thus limiting the applicability of top-down proteomics on a large scale.Bottom-up proteomics approaches have broad application because peptides are easier to separate and analyze via LC coupled with tandem mass spectrometry (MS/MS), offering a basis for more comprehensive protein identification. As this method relies on protein digestion (which produces multiple peptides for each protein), the sample complexity can become exceedingly large, requiring several dimensions of chromatographic separations (e.g. strong cation exchange and/or high pH reversed phase) prior to the final LC separation (typically reversed phase (RP)¹ C₁₈), which is oftentimes directly coupled with the mass spectrometer (3, 8). In general, the bottom-up analysis rarely achieves 100% sequence coverage of the original proteins, which can result in an incorrect/incomplete assessment of protein isoforms and combinatorial PTMs. Additionally, the digested peptides are not detected with uniform efficiency, which challenges and distorts protein quantification efforts.Because the data obtained from top-down and bottom-up work flows are complementary, several attempts have been made to integrate the two strategies (9, 10). Typically, these efforts have utilized extensive fractionation of the intact protein separation followed by bottom-up analysis of the collected fractions. Results so far have encouraged us to consider on-line digestion methods for integrating top-down and bottom-up proteomics in a higher throughput fashion. Such an on-line digestion approach would not only benefit in terms of higher sample throughput and improved overall sensitivity but would also allow a better correlation between the observed intact protein and its peptide digestion products, greatly aiding data analysis and protein characterization efforts.So far, however, none of the on-line integrated methods have proven robust enough for routine high throughput analyses. One of the reasons for this limited success relates to the choice of the proteolytic enzyme used for the bottom-up segment. Trypsin is by far the most widely used enzyme for proteome analyses because it is affordable (relative to other proteases), it has been well characterized for proteome research, and it offers a nice array of detectable peptides due to a fairly even distribution of lysines and arginines across most proteins. However, protein/peptide RPLC separations (optimal at low pH) are fundamentally incompatible with on-line trypsin digestion (optimal at pH ∼ 8) (11, 12). Therefore, on-line coupling of trypsin digestion and RPLC separations is fraught with technological challenges, and proposed solutions (12) have not proven to be robust enough for integration into demanding high throughput platforms.Our approach to this challenge was to investigate alternative proteases that may be more compatible with automated on-line digestion, peptide separation, and MS detection. Pepsin, which is acid-compatible (i.e. it acts in the stomach to initially aid in the digestion of food) (13), is a particularly promising candidate. This protease has previously been successfully used for the targeted analyses of protein complexes, hydrogen/deuterium exchange experiments (14, 15), and characterization of biopharmaceuticals (16, 17). Generally, pepsin preferentially cleaves the peptide bond located on the N-terminal side of hydrophobic amino acids, such as leucine and phenylalanine, although with less specificity than the preferential cleavage observed for trypsin at arginine and lysine. The compatibility of pepsin with typical LC-MS operation makes it an ideal choice for the development of novel approaches combining protein digestion, protein/peptide separation, and MS-based protein/peptide identification.To develop an automated system capable of simultaneously capturing top-down and bottom-up data, enzyme kinetics of the chosen protease must be extremely fast (because one cannot wait hours as is typical when performing off-line proteolysis). Another requirement is the use of immobilized enzyme or a low enough concentration of the enzyme such that autolysis products do not obscure the detection of substrate peptides. The latter was a concern when using pepsin because prior hydrogen/deuterium exchange experiments used enzyme:substrate ratios up to 1:2 (18, 19). To test whether or not such a large concentration of pepsin was necessary, we performed pepsin digestion at ratios of 1:20. Many alternative energy inputs into the system were considered for speeding up the digestion. For instance, it has been shown that an input of ultrasonic energy could accelerate the reaction rate of a typical trypsin digestion while using small amounts of a protease (20). Because ultrasonic energy results in an increase of temperature and microenvironments of high pressure, it has been hypothesized that the higher temperature was the component responsible for the enhanced enzyme activity (21). López-Ferrer et al. (22, 23), however, have demonstrated that application of higher pressure with incorporation of a Barocycler alone can make trypsin display faster enzyme kinetics. This phenomenon can easily be integrated with an LC separation (which already operates at elevated pressure) to enable an automatable ultrarapid on-line digestion LC-MS proteomics platform. Herein, we refer to this platform as the fast on-line digestion system (FOLDS) (23). Although FOLDS has been described before using trypsin, here the system is characterized with pepsin, and the results obtained are compared with results attainable with trypsin. Like trypsin, pepsin produced efficient protein digestion in just a few minutes when placed under pressure. Because of the natural maximal activity of pepsin at low pH, the FOLDS can be incorporated with a RePlay (Advion Biosciences, Ithaca, NY) system, and this powerful combination is what ultimately makes the integration of top-down and bottom-up proteomics analyses possible. The integrated analysis begins with a chromatographic separation of intact proteins. The separated proteins are then split into two streams. One stream proceeds directly to the mass spectrometer for MS and/or tandem MS analysis. The second stream is split into a long capillary where the chromatographic separation of the proteins is maintained, but their arrival to the mass spectrometer for detection is delayed. This is in essence the concept of RePlay (24, 25). Herein, we have taken the RePlay a step further by implementing our FOLDS technology into the second split delayed stream of proteins. While these delayed proteins travel down the long and narrow capillary, we exposed them to pepsin where, in combination with the pressure, the proteins are quickly and reproducibly digested. These peptide fragments are subsequently subjected to MS and/or tandem MS analysis. The FOLDS RePlay system allows the rapid and robust incorporation of the integrated top-down bottom-up proteomics work flow with the ability to not only identify proteins but also to sequence multisite/combinatorial PTMs because all detected peptides (from the FOLDS analysis) are confined to the original chromatographic peak of the protein they were derived from. The analysis of protein mixtures using this integrated strategy reduces the total amount of samples required to obtain both the top-down and bottom-up data, increases throughput, and improves protein sequence coverage.     

Copper Affects the Cotyledonary Carbohydrate Status During the Germination of Bean Seed

Seeds of bean (Phaseolus vulgaris L.) were germinated by soaking in distilled water or copper chloride solution. The relationships among copper excess treatment, germination rate, dry weight, sugar contents, and carbohydrase activities in cotyledon were investigated. Heavy metal stress provoked a diminution in germination rate and biomass mobilization, as compared with the control. A drastic disorder in soluble sugars export, especially glucose and fructose liberation, was also imposed after exposure to excess copper. This restricted the starch and sucrose breakdown in reserve tissue, as evidenced by the inhibition in the activities of α-amylase and invertase isoenzymes (soluble acid, soluble neutral, cell wall-bound acid).     

The <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis> response regulator ARR22 is a putative AHP phospho-histidine phosphatase expressed in the chalaza of developing seeds

Background  

The Arabidopsis response regulator 22 (ARR22) is one of two members of a recently defined novel group of two-component system (TCS) elements. TCSs are stimulus perception and response modules of prokaryotic origin, which signal by a His-to-Asp phosphorelay mechanism. In plants, TCS regulators are involved in hormone response pathways, such as those for cytokinin and ethylene. While the functions of the other TCS elements in Arabidopsis, such as histidine kinases (AHKs), histidine-containing phosphotransfer proteins (AHPs) and A-type and B-type ARRs are becoming evident, the role of ARR22 is poorly understood.     

MRI Features in a Canine Model of Ischemic Stroke: Correlation between Lesion Volume and Neurobehavioral Status during the Subacute Stage

The purpose of this study was to evaluate the diagnostic value of magnetic resonance imaging (MRI) and assess the correlation between the volume of the ischemic lesion and neurobehavioral status during the subacute stage of ischemic stroke. Ischemic stroke was induced in 6 healthy laboratory beagles through permanent occlusion of the middle cerebral artery (MCAO). T2-weighted and fluid-attenuated inversion recovery (FLAIR) imaging, diffusion-weighted imaging (DWI), measurement of the apparent diffusion coefficient (ADC) ratio, and neurobehavioral evaluation were performed 3 times serially by using a 1.5-T MR system: before and 3 and 10 d after MCAO. Ischemic lesions demonstrated T2 hyperintensity, FLAIR hyperintensity, and DWI hyperintensity. The ADC ratio was decreased initially but then was increased at 10 d after MCAO. Ischemic lesion volumes on T2-weighted and FLAIR imaging were not significantly different from those on DWI. The lesion volume and neurobehavioral score showed strong correlation. Our results suggest that conventional MRI may be a reliable diagnostic tool during the subacute stage of canine ischemic stroke.Abbreviations: ADC, apparent diffusion coefficient; DWI, diffusion-weighted imaging; FLAIR, fluid-attenuated inversion recovery; MCAO, middle cerebral artery occlusion; MRI, magnetic resonance imaging; PWI, perfusion-weighted imagingIn human medicine, stroke is a leading cause of adult mortality and neurologic disability worldwide.¹ Strokes previously were thought to be uncommon in small animals, but the true prevalence is unknown.⁴ These events are now recognized more frequently in dogs because of increased use of magnetic resonance imaging (MRI).^5,14,17Because the infusion of thrombolytic agents, such as urokinase or tissue plasminogen activator, within 3 to 6 h of the onset symptoms is effective in restoring blood flow and improving stroke outcome in humans,¹⁹ the detection of early ischemic changes is now thought to be necessary to improve patient outcome. Computed tomography and conventional MRI are not sufficiently sensitive to predict the presence and extent of ischemic damage during the acute stage after a stroke.^12,20 Therefore several MRI sequences, such as fluid-attenuated inversion recovery (FLAIR), diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), and MR angiography, have been developed for early diagnosis and subsequent follow-up of ischemic stroke.³ High-field magnetic strengths (at least 1.5 T) are necessary to perform these sequences.In contrast to the situation in humans, ischemic stroke in many dogs is diagnosed during the subacute stage—24 h to 6 wk after the vascular insult—due to the time lag between the onset of clinical signs to referral and to the lack of standard diagnostic protocols for ischemic stroke in dogs. In most reports of strokes in dogs, the median interval between the onset of neurologic dysfunction and performance of an MRI was more than 2 d.^5,14,17 Whereas DWI has marked sensitivity to very early ischemic changes in the brain, T2-weighted and FLAIR images gradually become more hyperintense later (that is, during the first 24 h after the insult).³ Therefore, hyperintensity on T2-weighted and FLAIR images is believed to be representative of mature lesions.¹⁵ In light of these findings, we hypothesized that conventional MR sequences, such as T2-weighted and FLAIR imaging as well as DWI would be used for the diagnosis of the subacute stage of ischemic stroke in dogs.The purpose of this study was to evaluate the diagnostic value of MRI and assess the correlation between the volume of ischemic lesions and neurobehavioral status during the subacute stage of ischemic stroke in dogs. We therefore investigated the lesion volume of T2-weighted and FLAIR images compared with that on DWI images. Furthermore, we assessed the relationship between the apparent diffusion coefficient (ADC) of the ischemic lesions and the neurobehavioral status of the dogs.     

Cyclin-dependent kinase 4 signaling acts as a molecular switch between syngenic differentiation and neural transdifferentiation in human mesenchymal stem cells

Multipotent mesenchymal stem/stromal cells (MSCs) are capable of differentiating into a variety of cell types from different germ layers. However, the molecular and biochemical mechanisms underlying the transdifferentiation of MSCs into specific cell types still need to be elucidated. In this study, we unexpectedly found that treatment of human adipose- and bone marrow-derived MSCs with cyclin-dependent kinase (CDK) inhibitor, in particular CDK4 inhibitor, selectively led to transdifferentiation into neural cells with a high frequency. Specifically, targeted inhibition of CDK4 expression using recombinant adenovial shRNA induced the neural transdifferentiation of human MSCs. However, the inhibition of CDK4 activity attenuated the syngenic differentiation of human adipose-derived MSCs. Importantly, the forced regulation of CDK4 activity showed reciprocal reversibility between neural differentiation and dedifferentiation of human MSCs. Together, these results provide novel molecular evidence underlying the neural transdifferentiation of human MSCs; in addition, CDK4 signaling appears to act as a molecular switch from syngenic differentiation to neural transdifferentiation of human MSCs.