Seasonality in foraging behaviour of Constrictotermes cyphergaster (Termitidae, Nasutitermitinae) in the Caatinga of Northeastern Brazil

The foraging activity of Constrictotermes cyphergaster was investigated in the Caatinga of Northeast Brazil. Eight colonies were monitored for seven days, during both dry and wet seasons. Foraging activity occurred in exposed columns at night, generally between 22:00 and 05:00 h. During the wet season, foraging activity was significantly higher, with one bout every 1.6 ± 0.2 days, than the dry season, when foraging bouts were performed every 1.9 ± 0.3 days. Foraging activity throughout the study colonies presented high temporal synchronization. In both seasons, foraging was negatively correlated with air temperature and positively correlated with humidity. The foraging trails were often re-utilized and ranged from 1 to 18.5 meters in length. No difference between seasons in the area potentially utilized by the study colonies was observed. Approximately 51000 individuals participated in the foraging bout during the dry season, whereas some 87000 individuals participated in the foraging bout during the wet season. This corresponds to 43 and 74% of the estimated total nest population for the dry and wet seasons respectively. The average ratio soldiers:workers during foraging was 1:1.2 in the dry season and 1:2 in the wet season. The higher frequency and number of individuals foraging during the wet season in the present study are likely to be a strategy from C. cyphergaster to store energy reserves to be utilized during the dry season. Received 28 November 2005; revised 29 May 2006 and 16 August 2006; accepted 1 September 2006.     

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

We report the use of neutron-encoded (NeuCode) stable isotope labeling of amino acids in cell culture for the purpose of C-terminal product ion annotation. Two NeuCode labeling isotopologues of lysine, ¹³C₆¹⁵N₂ and ²H₈, which differ by 36 mDa, were metabolically embedded in a sample proteome, and the resultant labeled proteins were combined, digested, and analyzed via liquid chromatography and mass spectrometry. With MS/MS scan resolving powers of ∼50,000 or higher, product ions containing the C terminus (i.e. lysine) appear as a doublet spaced by exactly 36 mDa, whereas N-terminal fragments exist as a single m/z peak. Through theory and experiment, we demonstrate that over 90% of all y-type product ions have detectable doublets. We report on an algorithm that can extract these neutron signatures with high sensitivity and specificity. In other words, of 15,503 y-type product ion peaks, the y-type ion identification algorithm correctly identified 14,552 (93.2%) based on detection of the NeuCode doublet; 6.8% were misclassified (i.e. other ion types that were assigned as y-type products). Searching NeuCode labeled yeast with PepNovo⁺ resulted in a 34% increase in correct de novo identifications relative to searching through MS/MS only. We use this tool to simplify spectra prior to database searching, to sort unmatched tandem mass spectra for spectral richness, for correlation of co-fragmented ions to their parent precursor, and for de novo sequence identification.The ability to make de novo sequence identifications directly from tandem mass spectra has long been a holy grail of the proteomic community. Such a capability would wean the field from its reliance upon sequenced genome databases. Even for organisms with fully annotated genomes, events such as single nucleotide polymorphisms, alternative splicing, gene fusion, and a host of other genomic transformations can result in altered proteomes. These alterations can vary from cell to cell and individual to individual. Thus, one could argue that the most valuable proteomic information, the individual and cellular proteome variation from the genome, remains elusive (1). This problem has received considerable attention; that said, it is not easy to de novo correlate spectrum to sequence in a large-scale, automated fashion (2–6). Improvements in mass accuracy have helped, but routine, reliable de novo sequencing without database assistance is not standard (7–10).A primary means to facilitate de novo spectral interpretation is the simple annotation of m/z peaks in tandem mass spectra as either N- or C-terminal. We and others have investigated this seemingly simple first step. Real-world spectra, however, are complex. Difficulties often arise in determining the charge state of the fragment or in differentiating between fragment ions and peaks arising from neutral loss, internal fragmentation, or spectral noise, both electronic and chemical. Several strategies have focused on product ion annotation. These approaches have included manipulation of the N-terminus basicity combined with electron transfer dissociation (ETD)¹ (11–13). This approach can yield mostly N-terminal fragments for peptides having only two charges. However, it requires both ETD and the protease LysN. Other methods have used differential labeling of N- and C-terminal peptides to shift either one or the other product ion series, by either metabolic or chemical means (14–18). Metabolic incorporation of amino acids is an efficient method of introducing distinctive labels that eliminates in vitro labeling, but this method requires that the sample be amenable to cell culture (19, 20). Additionally, it may be difficult to achieve complete labeling in complex systems. Several other approaches used to introduce heavy isotopes onto one terminus have been investigated, including trypsin digestion in ¹⁸O water (21–23), differential isotopic esterification (24, 25), derivatization of the C-terminal carboxylate by p-bromophenethylamine (8, 26), N-terminal derivatization with sulfonic acid groups (27, 28), and formaldehyde labeling via reductive amination (29–31). These chemical modifications are introduced after cell lysis, often immediately prior to analysis. Although chemical labeling strategies can be used with a variety of samples, difficulties can arise from differences in labeling efficiency between samples, and often a clean-up step is required following labeling, which may lead to sample loss. No matter the labeling method, in this regime, the two precursors must be separately isolated, fragmented, and analyzed either together or separately. The recognition and selection of the broadly spaced doublet in real time also are necessary. These requirements have limited the utility of these approaches. Our own laboratory discovered that the c- and ^●z-type product ions generated from either electron capture dissociation or ETD have distinct chemical formulae and therefore can always be distinguished based on accurate mass alone (32). The problem with this approach is that extremely high mass accuracy (<500 ppb) is required in order to distinguish these product ion types above ∼600 Da in mass. Thus, the majority of the product ions within a spectrum cannot be readily mapped to either terminus with high confidence.Despite these difficulties, we assert that robust de novo sequencing methodology would benefit greatly from a simple method that could be used to distinguish N- and C-terminal product ions with high accuracy and precision. Ideally, the approach would work regardless of the choice of proteolytic enzyme or dissociation method. Recently, we described a new technology for protein quantification called neutron encoding (NeuCode) (33). NeuCode embeds millidalton mass differences into peptides and proteins by exploiting the mass defect induced by differences in the nuclear binding energies of the various stable isotopes of common elements such as C, N, H, and O. For example, consider the amino acid lysine, which has eight additional neutrons (+8 Da). One way to synthesize this amino acid is to add six ¹³C atoms and two ¹⁵N atoms (+8.0142 Da). Another isotopologue could be constructed by adding eight ²H atoms (+8.0502). These two isotopologues differ by only 36 mDa; peptide precursors containing both of these amino acids would appear as a single, unresolved precursor m/z peak at a mass resolving power of less than ∼100,000. However, under high resolving powers (i.e. greater than ∼100,000 at m/z 400), this doublet is resolved. We first developed this NeuCode concept in the context of metabolic labeling, akin to stable isotope labeling with amino acids in cell culture (SILAC), except that instead of the precursor partners being separated by 4 to 8 Da, they are separated by only 6 to 40 mDa. For quantitative purposes, NeuCode promises to deliver ultraplexed SILAC (>12) without increasing spectral complexity.We reasoned that the isotopologues of Lys that permit NeuCode SILAC would generate a distinct fingerprint on C-terminal product ions. Specifically, peptides that have been labeled with NeuCode SILAC and digested with LysC uniformly contain Lys at the C terminus. Upon MS/MS, all C-terminal product ions should present as doublets (with duplex NeuCode), whereas N-terminal products will be detected as a single m/z peak. The very close m/z spacing of the NeuCode SILAC partners will ensure that each partner is always co-isolated and that the signatures are visible only upon high-resolving-power mass analysis. Here we investigate the combination of NeuCode SILAC and high-resolving-power MS/MS analysis to allow the straightforward identification of C-terminal product ions.

Sample Preparation

Saccharomyces cerevisiae strain BY4741 Lys1Δ was grown in defined synthetic complete (SC, Sunrise Science, San Diego, CA) drop-out media with either heavy 6C¹³/2N¹⁵ lysine (+8.0142 Da, Cambridge Isotopes, Tewksbury, MA), or heavy 8D (+8.0502 Da, Cambridge Isotopes). Cells were propagated to a minimum of 10 doublings. At mid-log phase, cells were harvested via centrifugation at 3,000 × g for 3 min and then washed three times with chilled double distilled H₂O. Cell pellets were resuspended in 5 ml lysis buffer (50 mm Tris pH 8, 8 m urea, 75 mm sodium chloride, 100 mm sodium butyrate, 1 mm sodium orthovanadate, protease and phosphatase inhibitor tablet), and protein was extracted via glass bead milling (Retsch, Haan, Germany). Protein concentration was measured via BCA (Pierce). Cysteines in the yeast lysate were reduced with 5 m dithiothreitol at ambient temperature for 30 min, alkylated with 15 mm iodoacetamide in the dark at ambient temperature for 30 min, and then quenched with 5 mm dithiothreitol. 50 mm tris (pH 8.0) was used to dilute the urea concentration to 4 m. Proteins were digested with LysC (1:50 enzyme:protein ratio) at ambient temperature for 16 h. The digestion was quenched with TFA and desalted with a tC18 Sep-Pak (Waters, Etten-Leur, The Netherlands). Samples were prepared by mixing 6C¹³/2N¹⁵ (+8.0412 Da) and 8D (+8.0502 Da) labeled peptides in 1:1 ratios by mass. For strong cation exchange fractionation, peptides were dissolved in 400 μl of strong cation exchange buffer A (5 mm KH₂PO₄ and 30% acetonitrile; pH 2.65) and injected onto a polysulfoethylaspartamide column (9.4 mm × 200 mm; PolyLC) attached to a Surveyor LC quarternary pump (Thermo Electron, West Chester, PA) operating at 3 ml/min. Peptides were detected by photodiode array detector (Thermo Electron, West Chester, PA). Fractions were collected every 2 min starting at 10 min into the following gradient: 0–2 min at 100% buffer A, 2–5 min at 0%–15% buffer B (5 mm KH₂PO₄, 30% acetonitrile, and 350 mm KCl (pH 2.65)), and 5–35 min at 15%–100% buffer B. Buffer B was held at 100% for 10 min. Finally, the column was washed with buffer C (50 mm KH₂PO₄ and 500 mm KCl (pH 7.5)) and water before recalibration. Fractions were collected by hand every 2 to 3 min starting at 10 min into the gradient and were lyophilized and desalted with a tC18 Sep-Pak (Waters).

LC-MS/MS

Samples were loaded onto a 15-cm-long, 75-μm capillary column packed with 5 μm Magic C18 (Michrom, Auburn, CA) particles in mobile phase A (0.2% formic acid in water). Peptides were eluted with mobile phase B (0.2% formic acid in acetonitrile) over a 120-min gradient at a flow rate of 300 nl/min. Eluted peptides were analyzed by an Orbitrap Elite mass spectrometer. For the nonfractionated samples, mass spectrometer instrument methods comprised one MS¹ scan followed by data-dependent MS² scans of the five most intense precursors. A survey MS¹ scan was performed by the Orbitrap at 30,000 resolving power to identify precursors to sample for tandem mass spectrometry, and this was followed by an additional MS¹ scan at 480,000 resolving power (at m/z 400; actual mass resolving power of 470,700). Data-dependent tandem mass spectrometry was performed via beam-type collisional activated dissociation (HCD) in the Orbitrap at a resolving power of 15,000, 60,000, 120,000, or 240,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. For experiments comparing the duty cycle and resolving power required in order to distinguish y-ion doublets, MS¹ and MS² target ion accumulation values were set to 5 × 10⁵ and 5 × 10⁴, respectively. For all other experiments, MS¹ target accumulation values were set to 1 × 10⁶ and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 30 s for −0.55 m/z and +2.55 m/z of selected precursors. For ETD analysis, data-dependent top-five mass spectrometry was performed at a resolving power of 240,000 (m/z 400; actual MS² mass resolving power of 271,000) (34). ETD accumulation values were set to 1 × 10⁶ for MS¹ target accumulation and 4 × 10⁵ for MS² target accumulation. The fluoranthene reaction time was set to 100 ms. For the high-pH strong cation exchange fractions, data-dependent tandem mass spectrometry was performed via HCD at a resolving power of either 60,000 or 120,000 and a collision energy of 30. Preview mode was enabled, and precursors of unknown charge or with a charge of +1 were excluded from MS² sampling. MS¹ targets were set to 1 × 10⁶, and MS² accumulation values were set to 4 × 10⁵. Dynamic exclusion was set to 45 s for −0.55 m/z and +2.55 m/z of selected precursors. Analysis by use of a wide isolation window was performed on an Orbitrap Fusion. MS¹ analysis was performed at 450,000 resolving power (m/z 200), and MS² analysis was performed at 120,000 resolving power (m/z 400). Data-dependent top-N mass spectrometry was performed, with precursors selected from sequential 25-Da windows. HCD was performed twice on the same precursor, first by use of a quadrupole isolation width of 0.7 m/z for peptide identification, and then using 25 m/z quadrupole isolation. Fragment ions were analyzed in the Orbitrap at a mass resolving power of 120,000 (m/z 400). MS¹ and MS² target accumulation values were set to 2 × 10⁵ and 5 × 10⁴, respectively.

Data Analysis

Thermo.raw files were converted to searchable DTA text files using the Coon OMSSA Proteomic Analysis Software Suite (COMPASS) (35). DTA files containing exclusively y-ions were generated using an in-house algorithm. DTA files were searched against the UniProt yeast database (version 132) with Lys-C specificity using the Open Mass Spectrometry Search Algorithm (OMSSA), version 2.1.9 (36). Methionine oxidation was searched as a variable modification. Cysteine carbamidomethylation and the mass shift imparted by the lysine isotopolgues were searched as fixed modifications. For MS² scans performed at a resolving power of 60,000, 120,000, or 240,000, a shift of +8.0142, representing the mass shift of the ¹³C₆¹⁵N₂ isotopologue, was searched. For MS² scans performed at 15,000 resolving power, the average shift of the ¹³C₆¹⁵N₂ and ⁸H₂ isotopologues (+8.0322) was searched. For all analyses, the precursor mass was obtained from the 480,000 MS scan. The precursor mass tolerance was defined as 50 ppm, and the fragment ion mass tolerance was set to 0.01 Da. A histogram of precursor mass error at different search tolerances is presented in supplemental Fig. S1. Using the COMPASS software suite, obtained search results were filtered to 1% FDR based on E-values. y-ion doublets were extracted from raw files using an in-house algorithm explained in the supplemental information. Briefly, an ensemble of three different machine learning models was used to score each MS/MS spectral peak for C-terminal product ion prediction. To train our ensemble learner to correctly distinguish C-terminal product ion peaks from N-terminal product ion peaks and noise peaks within our experimental MS/MS spectra, we generated a representative training set of spectral data. Instances used for training and test sets were peaks acquired only from MS/MS spectra associated with a peptide identification. Peaks with a signal-to-noise value of less than 5 were not used. Feature information for each training/testing instance was extracted from raw spectral data. Seven MS/MS spectral features were selected to generate training and test set data: (1) “has doublet” (evaluated as “true” only if a spectral peak could be found at the predicted m/z of the peak''s “heavy” partner), (2) “signal-to-noise” (discretized using a scale of 1–5 based on the peak''s signal-to-noise value), (3) “is isotope,” (4) “is neutral loss,” (5) “number of isotopes,” (6) “number of doublet isotopes,” and (7) “has neutral loss.”To evaluate NeuCode SILAC labeling for automated de novo sequencing, PepNovo⁺ (8) was benchmarked on y-ion predicted spectra. First, a set of identified spectra from 13,832 unique peptides (>7,400 per precursor charge 2–3) was produced to train PepNovo⁺ so it could learn features such as the relative peak height ranks of b/y-ions and the probability of noise at each mass interval. These training spectra were acquired under the 11 NeuCode yeast strong cation exchange fractions prepared as described above. Thermo raw files were converted into mzXML format using ProteoWizard v2.2.2828 (with peak-picking turned on) and identified by MS-GF⁺ v9358 (37) at a 1% spectrum-level FDR against the UniProt yeast database (plus isoforms), v20110729. A fixed modification of K⁺8.0142 was imposed along with variable modifications of oxidized Met and deamidated Asn/Gln. All MS/MS scans were searched with a 50-ppm precursor mass tolerance, the high-accuracy LTQ instrument setting, the HCD fragmentation setting, and one allowed missed Lys-C cleavage.Thermo.raw files were also converted into DTA spectra as before, except the in-house algorithm for selecting y-ion doublets was slightly altered to boost the peak height of predicted y-ions above that of other peaks (the cumulative peak height was equal to the sum of the monoisotopic doublet peaks, all isotopic doublet peaks, and two times the peak height of the base peak) and to convert their m/z to charge one. Remaining peaks not predicted to be y-ions were converted to charge one by a previously described MS/MS deconvolution tool (38). Deconvoluted DTA spectra that originated from identified MS/MS scans were then paired with the MSGF⁺ peptide IDs and passed to PepNovo⁺ for training. The resulting PepNovo⁺ scoring model lacked the rank-boosting component (39), which requires identified spectra from >100,000 unique peptides per precursor charge state and extensive modification of the PepNovo⁺ source code to train. Still, the model was sufficient to perform de novo peptide sequencing on the y-ion predicted spectra. PepNovo⁺ was also run on the raw MS/MS scans (mzXML spectra converted to MGF with all MS/MS peaks converted to charge one) by use of a previously trained HCD scoring model that also lacks the rank-boosting component (40). The following PepNovo⁺ parameters were set at all stages of training and benchmarking: fixed modification of K⁺8.0142; variable modifications of oxidized Met and deamidated Asn; 0.01-Da fragment mass tolerance; use of spectrum precursor charge; and use of spectrum precursor m/z.     

The influence of fire frequency on the structure and botanical composition of savanna ecosystems

Savannas cover 60% of the land surface in Southern Africa, with fires and herbivory playing a key role in their ecology. The Limpopo National Park (LNP) is a 10,000 km² conservation area in southern Mozambique and key to protecting savannas in the region. Fire is an important factor in LNP's landscapes, but little is known about its role in the park's ecology. In this study, we explored the interaction between fire frequency (FF), landscape type, and vegetation. To assess the FF, we analyzed ten years of the Moderate resolution Imaging Spectroradiometer (MODIS) burned area product (2003–2013). A stratified random sampling approach was used to assess biodiversity across three dominant landscapes (Nwambia Sandveld‐NS, Lebombo North‐LN, and Shrubveld Mopane on Calcrete‐C) and two FF levels (low—twice or less; and high—3 times or more, during 10 years). Six ha were sampled in each stratum, except for the LN versus high FF in which low accessibility allowed only 3 ha sampling. FF was higher in NS and LN landscapes, where 25% and 34% of the area, respectively, burned more than three times in 10 years. The landscape type was the main determinant of grass composition and biomass. However, in the sandy NS biomass was higher under high FF. The three landscapes supported three different tree/shrub communities, but FF resulted in compositional variations in NS and LN. Fire frequency had no marked influence on woody structural parameters (height, density, and phytomass). We concluded that the savannas in LNP are mainly driven by landscape type (geology), but FF may impose specific modifications. We recommend a fire laissez‐faire management system for most of the park and a long‐term monitoring system of vegetation to address vegetation changes related to fire. Fire management should be coordinated with the neighboring Kruger National Park, given its long history of fire management. Synthesis: This study revealed that grass and tree/shrub density, biomass, and composition in LNP are determined by the landscape type, but FF determines some important modifications. We conclude that at the current levels FF is not dramatically affecting the savanna ecosystem in the LNP (Figure 1). However, an increase in FF may drive key ecosystem changes in grass biomass and tree/shrub species composition, height, phytomass, and density.     

Origins of bone repair in the armour of fossil fish: response to a deep wound by cells depositing dentine instead of dermal bone

The outer armour of fossil jawless fishes (Heterostraci) is, predominantly, a bone with a superficial ornament of dentine tubercles surrounded by pores leading to flask-shaped crypts (ampullae). However, despite the extensive bone present in these early dermal skeletons, damage was repaired almost exclusively with dentine. Consolidation of bone, by dentine invading and filling the vascular spaces, was previously recognized in Psammolepis and other heterostracans but was associated with ageing and dermal shield wear (reparative). Here, we describe wound repair by deposition of dentine directly onto a bony scaffold of fragmented bone. An extensive wound response occurred from massive deposition of dentine (reactionary), traced from tubercle pulp cavities and surrounding ampullae. These structures may provide the cells to make reparative and reactionary dentine, as in mammalian teeth today in response to stimuli (functional wear or damage). We suggest in Psammolepis, repair involved mobilization of these cells in response to a local stimulatory mechanism, for example, predator damage. By comparison, almost no new bone is detected in repair of the Psammolepis shield. Dentine infilling bone vascular tissue spaces of both abraded dentine and wounded bone suggests that recruitment of this process has been evolutionarily conserved over 380 Myr and precedes osteogenic skeletal repair.     

Atorvastatin and Fluoxetine Prevent Oxidative Stress and Mitochondrial Dysfunction Evoked by Glutamate Toxicity in Hippocampal Slices

Atorvastatin has been shown to exert a neuroprotective action by counteracting glutamatergic toxicity. Recently, we have shown atorvastatin also exerts an antidepressant-like effect that depends on both glutamatergic and serotonergic systems modulation. Excitotoxicity is involved in several brain disorders including depression; thus, it is suggested that antidepressants may target glutamatergic system as a final common pathway. In this study, a comparison of the mechanisms involved in the putative neuroprotective effect of a repetitive atorvastatin or fluoxetine treatment against glutamate toxicity in hippocampal slices was performed. Adult Swiss mice were treated with atorvastatin (10 mg/kg, p.o.) or fluoxetine (10 mg/kg, p.o.), once a day during seven consecutive days. On the eighth day, animals were killed and hippocampal slices were obtained and subjected to an in vitro protocol of glutamate toxicity. An acute treatment of atorvastatin or fluoxetine was not neuroprotective; however, the repeated atorvastatin or fluoxetine treatment prevented the decrease in cellular viability induced by glutamate in hippocampal slices. The loss of cellular viability induced by glutamate was accompanied by increased D-aspartate release, increased reactive oxygen species (ROS) and nitric oxide (NO) production, and impaired mitochondrial membrane potential. Atorvastatin or fluoxetine repeated treatment also presented an antidepressant-like effect in the tail suspension test. Atorvastatin or fluoxetine treatment was effective in protecting mice hippocampal slices from glutamate toxicity by preventing the oxidative stress and mitochondrial dysfunction.     

Evolution of Volatile Emission in Rhus coriaria Organs During Different Stages of Growth and Evaluation of the Essential Oil Composition

Rhus coriaria, also known as Sumac, has been traditionally used in many countries as spice, condiment, dying agent, and medicinal herb. The chemical composition of essential oils (EOs) and the volatile emissions from different organs of this species collected in Sicily (Italy) were analyzed by gas chromatography‐flame ionization detection and gas chromatography/mass spectrometry. Monoterpene and sesquiterpene hydrocarbons were the most abundant class in the volatile emissions with β‐caryophyllene and α‐pinene were the main constituents in the majority of the examined samples. The EO composition was characterized by high amount of monoterpene and sesquiterpene hydrocarbons together with diterpenes. The main compounds in the EO obtained from the leaves and both stages of fruit maturation were cembrene and β‐caryophyllene, while α‐pinene and tridecanoic acid were the key compounds in the flower EO. All the data were submitted to multivariate statistical analysis showing many differences among the different plant parts and their ontogenetic stages.     

Neuroprotective Effects of Chalcones from <Emphasis Type="Italic">Myracrodruon urundeuva</Emphasis> on 6-Hydroxydopamine-Induced Cytotoxicity in Rat Mesencephalic Cells

In the present work, we showed that a chalcone-enriched fraction (CEF) isolated from the stem bark of a Brazilian medicinal plant, Myracrodruon urundeuva, presents neuroprotective actions on 6-hydroxydopamine (6-OHDA)-induced neuronal cell death, in rat mesencephalic cells. In the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium] assay, which is an index of cell viability, CEF (1–100 μg/ml) reversed in a concentration-dependent manner the 6-OHDA-induced cell death. While cells exposed to 6-OHDA (40 μM) showed an increased concentration of thiobarbituric acid reactive substances (TBARS), the pretreatment with CEF (10–100 μg/ml) significantly decreased the 6-OHDA-induced TBARS formation, indicative of a neuroprotection against lipoperoxidation. Furthermore, the drastic increase of nitrite levels induced by 6-OHDA, indicative of nitric oxide formation and free radicals production, was prevented by CEF. Double staining with acridine orange/ethidium bromide showed that cultures exposed to 6-OHDA (40 and 200 μM) presented an increase of apoptotic and necrotic cell numbers in a concentration-dependent manner. CEF (100 μg/ml) protected cells from apoptosis and necrosis and increased number of cells presenting a normal morphology. The immunohistochemical analysis for tyrosine hydroxylase (TH) positive neurons indicated that 6-OHDA (40 and 200 μM) caused a concentration-dependent loss of TH+ and TH− neurons. CEF protected both cells types from 6-OHDA-induced cell death. All together, our results demonstrated neuroprotective effects of chalcones, which are able to reduce oxidative stress and apoptotic injury caused by 6-OHDA. Our findings suggest that chalcones could provide benefits, along with other therapies, in neurodegenerative injuries, such as Parkinson’s disease.     

Effects of different mesenchymal stromal cell sources and delivery routes in experimental emphysema

We sought to assess whether the effects of mesenchymal stromal cells (MSC) on lung inflammation and remodeling in experimental emphysema would differ according to MSC source and administration route. Emphysema was induced in C57BL/6 mice by intratracheal (IT) administration of porcine pancreatic elastase (0.1 UI) weekly for 1 month. After the last elastase instillation, saline or MSCs (1×10⁵), isolated from either mouse bone marrow (BM), adipose tissue (AD) or lung tissue (L), were administered intravenously (IV) or IT. After 1 week, mice were euthanized. Regardless of administration route, MSCs from each source yielded: 1) decreased mean linear intercept, neutrophil infiltration, and cell apoptosis; 2) increased elastic fiber content; 3) reduced alveolar epithelial and endothelial cell damage; and 4) decreased keratinocyte-derived chemokine (KC, a mouse analog of interleukin-8) and transforming growth factor-β levels in lung tissue. In contrast with IV, IT MSC administration further reduced alveolar hyperinflation (BM-MSC) and collagen fiber content (BM-MSC and L-MSC). Intravenous administration of BM- and AD-MSCs reduced the number of M1 macrophages and pulmonary hypertension on echocardiography, while increasing vascular endothelial growth factor. Only BM-MSCs (IV > IT) increased the number of M2 macrophages. In conclusion, different MSC sources and administration routes variably reduced elastase-induced lung damage, but IV administration of BM-MSCs resulted in better cardiovascular function and change of the macrophage phenotype from M1 to M2.     

Expanding Proteome Coverage with Orthogonal-specificity α-Lytic Proteases

Bottom-up proteomics studies traditionally involve proteome digestion with a single protease, trypsin. However, trypsin alone does not generate peptides that encompass the entire proteome. Alternative proteases have been explored, but most have specificity for charged amino acid side chains. Therefore, additional proteases that improve proteome coverage through cleavage at sequences complementary to trypsin''s may increase proteome coverage. We demonstrate the novel application of two proteases for bottom-up proteomics: wild type α-lytic protease (WaLP) and an active site mutant of WaLP, M190A α-lytic protease (MaLP). We assess several relevant factors, including MS/MS fragmentation, peptide length, peptide yield, and protease specificity. When data from separate digestions with trypsin, LysC, WaLP, and MaLP were combined, proteome coverage was increased by 101% relative to that achieved with trypsin digestion alone. To demonstrate how the gained sequence coverage can yield additional post-translational modification information, we show the identification of a number of novel phosphorylation sites in the Schizosaccharomyces pombe proteome and include an illustrative example from the protein MPD2 wherein two novel sites are identified, one in a tryptic peptide too short to identify and the other in a sequence devoid of tryptic sites. The specificity of WaLP and MaLP for aliphatic amino acid side chains was particularly valuable for coverage of membrane protein sequences, which increased 350% when the data from trypsin, LysC, WaLP, and MaLP were combined.The most powerful technique for system-scale protein measurement, or proteomics, is mass-spectrometry-based proteomics (1). Although great progress has enabled the quantification of nearly all proteins expressed in yeast (2, 3), sequence coverage is often dismal, with some proteins being identified by a single peptide sequence. Complete amino acid coverage is valuable for comprehensive profiling of post-translational modifications (e.g. phosphorylation) and for quantification of splice variants. Low observed proteome coverage can be caused by several factors, including the wide dynamic range of protein concentrations in biological samples, splice variants, and unanticipated or unconsidered post-translational modifications (PTMs).¹ Improvements to every step of the bottom-up proteomics workflow continue to increase the observable proteome.Because of length constraints that limit observable peptides, proteome coverage is ultimately limited by proteome digestion. Typically, identifiable peptides are between 7 and 35 amino acids in length, with the lower limit being determined by sequence uniqueness and the upper limit being determined by the instrument''s resolving power (4). In silico proteome digestions predict that nearly one-quarter of peptides generated from tryptic digestion of the Saccharomyces cerevisiae proteome will be only a single amino acid long. Sequences lost due to length overall result in a theoretical upper proteome coverage limit of 68.8% according to in silico predictions (supplemental Fig. S1).Recently, several groups have demonstrated that combining data from separate protease digestions improves proteome coverage (4–7). Improved peptide yield was also shown, allowing proteome analysis of small-quantity samples from laser-capture microdissection (8, 9). Swaney et al. used trypsin, Lys-C, Arg-C, Glu-C, and Asp-N to double the observed S. cerevisiae nonredundant amino acid coverage from 11.9% to 25.5% (4).Other proteases that are used in proteomics to complement trypsin mainly cleave at ionic amino acid side chains, and it would be useful to have proteases with additional, complementary specificities. Here we demonstrate the application of wild-type α-lytic protease (WaLP) (10) and an active site mutant of WaLP, M190A α-lytic protease (MaLP) (11), to proteome digestion for shotgun proteomics. Both were reported to have specificity for cleaving after aliphatic side chains, which are more common amino acids. WaLP is a serine protease secreted from the soil bacteria Lysobacter enzymogenesis (10, 12) and has been studied extensively via mutagenesis and biophysical methods (11). WaLP has been found to exhibit remarkable stability (13, 14).Non-tryptic peptides are more difficult to identify than tryptic peptides, especially when lacking defined termini (i.e. from semi-specific protease digestion or endogenous peptides) due to increased database search space and less predictable ionization and fragmentation. A lack of defined termini drastically increases database search space because more possible peptides fall within the precursor tolerance and drive up false positive rates (15). The majority of tryptic peptides have one positive charge localized at each terminus in a +2 precursor charge state upon electrospray ionization, which results in well-characterized fragmentation by collision-induced dissociation (CID) (16, 17). Non-tryptic peptides, in contrast, may lack positively charged side chains (i.e. Arg, Lys, His) altogether, making it unlikely that multiple charges will be obtained upon electrospray ionization. Those that do contain positive charges away from the C terminus produce less predictable fragmentation upon CID. Recently, additional peptide fragmentation methods have become accessible, such as electron-transfer dissociation (ETD) (18), which produces fragment ion series that are less dependent on peptide sequence, and higher-energy collisional dissociation (HCD) (19). An in-depth comparison of activation methods for non-tryptic peptide identification has been published recently by Smith''s lab. In that report the authors evaluated FT-CID, FT- ETD, and FT-HCD for sequencing peptides isolated from blood plasma (20).To enable application of the α-lytic proteases with specificity for aliphatic amino acid side chains to shotgun proteomics, we address the above issues by comparing multiple fragmentation modes in combination with the peptide identification algorithm MS-GFDB, which easily learns scoring parameters from an initial set of annotated peptide-spectrum matches for arbitrary fragmentation methods and proteases (21). We analyzed standard protein mixtures and complex Schizosaccharomyces pombe proteomes digested with trypsin, LysC, WaLP, and MaLP. Specifically, we assessed ion activation methods, observed peptide character, and biological gains due to additional digestions. The results present the pros and cons of using orthogonal proteases in proteomics.