Immune and behavioral consequences of microglial reactivity in the aged brain

Bidirectional communication between the immune system and the brain is essential for mounting the appropriate immunological, physiological, and behavioral responses to immune activation. Aging, however, may impair this important bi-directional interaction. In support of this notion, peripheral infection in the elderly is associated with an increased frequency of behavioral and cognitive complications. Recent findings in animal models of aging and neurodegenerative disease indicate that microglia, innate immune cells of the brain, become primed or reactive. Understanding age- and disease-associated alterations in microglia is important because glia (microglia and astrocytes) play an integral role in propagating inflammatory signals that are initiated in the periphery. In this capacity, brain glia produce inflammatory cytokines that target neuronal substrates and elicit a sickness-behavior syndrome that is normally beneficial to the host organism. Increased reactivity of microglia sets the stage for an exaggerated neuroinflammatory cytokine response following activation of the peripheral innate immune system, which may underlie subsequent long-lasting behavioral and cognitive deficits. In support of this premise, recent findings indicate that stimulation of the peripheral immune system in aged rodents causes exaggerated neuroinflammation that is paralleled by cognitive impairment, prolonged sickness, and depressive-like complications. Therefore, the purpose of this review is to discuss the new evidence that age-associated priming of microglia could play a pathophysiological role in exaggerated behavioral and cognitive sequelae to peripheral infection.     

Design and synthesis of novel pyrimidine hydroxamic acid inhibitors of histone deacetylases

Inhibition of histone deacetylase activity represents a promising new modality in the treatment of a number of cancers. A novel HDAC series demonstrating inhibitory activity in cell proliferation assays is described. Optimisation based on the introduction of basic amine linkers to effect good drug distribution to tumour led to the identification of a compound with oral activity in a human colon cancer xenograft study associated with increased histone H3 acetylation in tumour tissue.     

Deconvolution and Database Search of Complex Tandem Mass Spectra of Intact Proteins: A COMBINATORIAL APPROACH*

Top-down proteomics studies intact proteins, enabling new opportunities for analyzing post-translational modifications. Because tandem mass spectra of intact proteins are very complex, spectral deconvolution (grouping peaks into isotopomer envelopes) is a key initial stage for their interpretation. In such spectra, isotopomer envelopes of different protein fragments span overlapping regions on the m/z axis and even share spectral peaks. This raises both pattern recognition and combinatorial challenges for spectral deconvolution. We present MS-Deconv, a combinatorial algorithm for spectral deconvolution. The algorithm first generates a large set of candidate isotopomer envelopes for a spectrum, then represents the spectrum as a graph, and finally selects its highest scoring subset of envelopes as a heaviest path in the graph. In contrast with other approaches, the algorithm scores sets of envelopes rather than individual envelopes. We demonstrate that MS-Deconv improves on Thrash and Xtract in the number of correctly recovered monoisotopic masses and speed. We applied MS-Deconv to a large set of top-down spectra from Yersinia rohdei (with a still unsequenced genome) and further matched them against the protein database of related and sequenced bacterium Yersinia enterocolitica. MS-Deconv is available at http://proteomics.ucsd.edu/Software.html.Top-down proteomics is a mass spectrometry-based approach for identification of proteins and their post-translational modifications (PTMs)1 (1–14). Unlike the “bottom-up” approach where proteins are first digested into peptides and then a peptide mixture is analyzed by mass spectrometry, the top-down approach analyzes intact proteins. Thus, it has advantages in detecting and localizing PTMs as well as identifying multiple protein species (e.g. proteolytically processed protein species). Despite its advantages, top-down proteomics presents many challenges. These include requirement of high sample quantity, sophisticated instrumentation, protein separation, and robust computational analysis tools. For this reason, top-down proteomics has rarely been used for analyzing complex mixtures (12–18), and it is typically used to study single purified proteins. However, this situation is quickly changing with recent top-down studies of complex protein mixtures (14, 19).Because of the existence of natural isotopes, fragment ions of the same chemical formula and charge state are usually represented by a collection of spectral peaks in tandem mass spectra called an isotopomer envelope. The monoisotopic mass of a chemical formula is the sum of the masses of the atoms using the principal (most abundant) isotope for each element. Spectral deconvolution focuses on grouping spectral peaks into isotopomer envelopes. By doing so, the charge state and monoisotopic mass of each envelope are effectively determined. A complex multi-isotopic peak list in the m/z space is translated into a simple monoisotopic mass list that is easier to analyze.Given the monoisotopic mass and charge state of a fragment ion, its theoretical isotopic distribution can be predicted by assuming the fragment ion has an average elemental composition with respect to its mass (20) or using its precise elemental composition if the protein is known. Exploiting this, many deconvolution methods use theoretical isotopic distributions to detect and evaluate candidate isotopomer envelopes, which is the envelope detection problem (Fig. 1). To evaluate the fit of a candidate envelope to its theoretical isotopic distribution, many metrics have been proposed (20–32).Open in a separate windowFig. 1.Envelope detection. a, a theoretical isotopic distribution is predicted with the monoisotopic mass and charge state of a fragment ion. b, an observed envelope is detected by mapping peaks in the theoretical distribution to the spectrum. c, match between the theoretical isotopic distribution and the observed envelope. d, the theoretical isotopic distribution is scaled (the intensities of the peaks are multiplied by a constant) to have the best fit with the intensities of peaks in the observed envelope. Finally, a score for the observed envelope can be computed by comparing it with the intensity-scaled theoretical isotopic distribution.The candidate envelopes often overlap and share peaks, leading to a combinatorial problem of selecting the list of envelopes that best explains the spectrum (Fig. 2). In contrast to the well studied envelope detection problem, the envelope selection problem remains poorly explored. Most deconvolution algorithms follow a simple greedy approach to selecting the set of envelopes where the highest scoring envelopes are iteratively selected and removed from the spectrum. Although this approach often generates reasonable sets of envelopes for simple spectra, its performance deteriorates in cases of complex spectra.Open in a separate windowFig. 2.Envelope selection problem. Overlapping envelopes lead to a difficult combinatorial problem of selecting an optimal set of envelopes. We illustrate two cases where a deconvolution method that follows a greedy envelope selection outputs the envelope E₂, whereas the optimal solution consists of the envelopes E₁ and E₃. Example a illustrates the case where envelopes do not share peaks, and example b illustrates the case where envelopes share a spectral peak (E₁ and E₃).In particular, the greedy approach performs well when the envelopes are distributed sparsely along the m/z axis. Large proteins have many fragments that appear in multiple charge states. The high number of envelopes/peaks and the small m/z spread of the fragments with high charge states result in narrow m/z regions with high peak density. In these peak-dense regions, envelopes may overlap and share peaks, and the greedy approach and even manual interpretation often fail to find the optimal combination of envelopes (supplemental Fig. 1).Several methods have been proposed to explore the envelope selection problem. McIlwain et al. (33) presented a dynamic programming algorithm for selecting a set of envelopes such that the m/z ranges of the envelopes do not overlap. This non-overlapping condition becomes too restrictive for complex spectra of intact proteins. Samuelsson et al. (34) proposed a method that follows a non-negative sparse regression scheme. Du and Angeletti (35) and Renard et al. (36) addressed the envelope selection problem as a statistical problem of variable selection and used LASSO to solve it.Here, we present MS-Deconv, a combinatorial algorithm for spectral deconvolution. MS-Deconv (i) generates a large set of candidate envelopes, (ii) constructs an envelope graph encoding all envelopes and relationships between them, and (iii) finds a heaviest path in the envelope graph. Although the envelope graph of a complex spectrum is large (exceeding a million nodes in some cases), the heaviest path algorithm can efficiently find an optimal set of envelopes. MS-Deconv explicitly scores combinations of candidate envelopes rather than individual envelopes as in previous approaches.We tested MS-Deconv on a data set of top-down spectra from known proteins and evaluated the monoisotopic masses recovered by MS-Deconv. A mass was classified as a true positive if it was matched to the monoisotopic mass of a theoretical fragment ion of the protein within a specific parts per million (ppm) tolerance. We compared the performance of MS-Deconv with the widely used Thrash (20) and Xtract (37) and demonstrated that, with a few exceptions, MS-Deconv recovers more true positive masses. For example, for the collisionally activated dissociation (CAD) spectrum of bacteriorhodopsin (BR) with charge 10, the percentage of true positive masses among the top 150 masses is above 70% for MS-Deconv and less than 50% for Thrash. Additionally, MS-Deconv is ∼33 times faster than Thrash and 4 times faster than Xtract. Furthermore, MS-Deconv implements some user-friendly features: (i) outputs the set of peptide sequence tags, (ii) provides protein and spectral annotations, and (iii) allows one to inspect the recovered envelopes. We also tested MS-Deconv on a large LC-MS/MS data set from Yersinia rohdei (with a still unsequenced genome) (19). Y. rohdei is a non-pathogenic bacterium that is often used as a simulant for the potential bioterrorism agent Yersinia pestis, the causative agent of plague. We applied MS-Deconv to extract monoisotopic mass lists from top-down spectra and compared the mass lists with those reported by Thrash. We used ProSightPC (38) and the spectral alignment algorithm (39) to identify related proteins from a protein database of Yersinia enterocolitica (with a closely related and sequenced genome). The results demonstrated that MS-Deconv reported more matched fragments than Thrash for most proteins. Additionally, using spectral alignment, we identified eight proteins in Y. rohdei that were not reported in the ProSightPC-based searches (19) of the Y. enterocolitica protein database.     

Increasing confidence of protein interactomes using network topological metrics

MOTIVATION: Experimental limitations in high-throughput protein-protein interaction detection methods have resulted in low quality interaction datasets that contained sizable fractions of false positives and false negatives. Small-scale, focused experiments are then needed to complement the high-throughput methods to extract true protein interactions. However, the naturally vast interactomes would require much more scalable approaches. RESULTS: We describe a novel method called IRAP* as a computational complement for repurification of the highly erroneous experimentally derived protein interactomes. Our method involves an iterative process of removing interactions that are confidently identified as false positives and adding interactions detected as false negatives into the interactomes. Identification of both false positives and false negatives are performed in IRAP* using interaction confidence measures based on network topological metrics. Potential false positives are identified amongst the detected interactions as those with very low computed confidence values, while potential false negatives are discovered as the undetected interactions with high computed confidence values. Our results from applying IRAP* on large-scale interaction datasets generated by the popular yeast-two-hybrid assays for yeast, fruit fly and worm showed that the computationally repurified interaction datasets contained potentially lower fractions of false positive and false negative errors based on functional homogeneity. AVAILABILITY: The confidence indices for PPIs in yeast, fruit fly and worm as computed by our method can be found at our website http://www.comp.nus.edu.sg/~chenjin/fpfn.     

In vitro studies on colonization resistance of the human gut microbiota to Candida albicans and the effects of tetracycline and Lactobacillus plantarum LPK

An anaerobic three-vessel continuous-flow culture system, which models the three major anatomical regions of the human colon, was used to study the persistence of Candida albicans in the presence of a faecal microbiota. During steady state conditions, overgrowth of C. albicans was prevented by commensal bacteria indigenous to the system. However antibiotics, such as tetracycline have the ability to disrupt the bacterial populations within the gut. Thus, colonization resistance can be compromised and overgrowth of undesirable microorganisms like C. albicans can then occur. In this study, growth of C. albicans was not observed in the presence of an established faecal microbiota. However, following the addition of tetracycline to the growth medium, significant growth of C. albicans occurred. A probiotic Lactobacillus plantarum LPK culture was added to the system to investigate whether this organism had any effects upon the Candida populations. Although C. albicans was not completely eradicated in the presence of this bacterium, cell counts were markedly reduced, indicating a compromised physiological function. This study shows that the normal gut flora can exert 'natural' resistance to C. albicans, however this may be diminished during antibiotic intake. The use of probiotics can help fortify natural resistance.     

Adventitious root formation in woody plant tissue: The influence of light and indole-3-butyric acid (IBA) on adventitious root induction in <Emphasis Type="Italic">Betula Pendula</Emphasis>

Summary The effects of auxin concentration and photoperiod on rooting were examined with a view to establishing a rooting regime for Betula pendula shoots cultured in vitro. Optimum concentrations of indole-3-butyric acid (IBA) were determined: the effects of a 16-h photoperiod and a pretreatment of 8d total darkness were examined. Maximum rooting rates and rooting densities (root number) were achieved using relatively low levels of IBA (0.39–0.74 μM). Both the dark and the light regimes produced roots, higher yields occurring with the latter. Maximum rooting percentage was reached after 30 d growth. in the light-treated cultures.     

OBSERVATIONS ON NAVICULA THALLODES (BACILLARIOPHYCEAE), A BLADE-FORMING DIATOM FROM THE BERING SEA1

A thallus-forming diatom, Navicula thallodes Proschkina-Lavrenko, previously known only from the original collection at Bering Island (U.S.S.R.), has been found at Amchitka Island in the Aleutians, Alaska. The most remarkable observation of the present report is that N. thallodes may form blades up to 50 cm long, which to our knowledge is the greatest length reported for a colonial diatom. SEM observations of this diatom are presented for the first time.     

Preparation of ferritin-avidin conjugates by reductive alkylation for use in electron microscopic cytochemistry.

An improved technique was developed for the unidirectional covalent binding of avidin to ferritin by reductive alkylation. The method is based on the oxidation of sugar moieties on avidin and subsequent coupling to amino groups of ferritin via Schiff's bases followed by reduction with sodium borohydride. The resultant conjugate was used as an ultrastructural marker for the localization of surface receptor sites on biotin-derivatized whole cells. Erythrocytes were treated chemically with sodium meta-periodate and biotin hydrazide in succession. The ferritin-avidin conjugates were used to label the biotin sites either before or after fixation of the cells. The density and distribution of ferritin avidin conjugates on cell surfaces were anlyzed on thin sections and compared with those of cationized ferritin, which were shown to bind anionic sites of the erythrocyte membrane. The extensions of this method for the visualization of other systems is discussed.