Experimental insights into age‐exacerbated cognitive dysfunction after peripheral surgery

Here I comment on the recent contribution by Barrientos et al. J. Neurosci. 32, 14641–14648 (2012) addressing treatment possibilities for surgery‐induced cognitive dysfunction. It has been over 15 years since the publication of a landmark study that indicated age as a major risk factor for postoperative cognitive dysfunction (POCD) (Moller et al., Lancet 351 , 857–861 1998). With increasing life expectancy, surgical procedures conducted in elderly persons are becoming more common. The prevalence of POCD may mean that some patients will exchange the incapacitating condition that led them to surgery in the first instance for another such condition, which has been created by the surgical procedure itself. The report by Barrientos and collaborators (2012) is a timely and welcome study that further examines treatment possibilities for surgery‐induced cognitive dysfunction. Future studies should address issues such as intensity and onset of inflammation within the brain and additional treatments possibilities beyond IL‐1‐ra.     

Cover Picture: Proteomics 6/2009

In this issue of Proteomics you will find the following highlighted articles: Keeping up with the lung cancers You're in good company if you smoke and develop lung cancer. The World Health Organization estimates 1.2 million new cases occur every year. On the other hand, 1.1 million people die from it every year‐bummer. One reason for the high death rate is the frequent development of resistance to several of the most commonly used drugs simultaneously. Multiple drug resistance (MDR) is the major cause of chemotherapeutic failure. Keenan et al. explored the proteomic changes associated with MDR failure (adriamycin) in a cultured lung cancer cell line (DLKP) and several subtypes. Adriamycin normally kills by blocking replication at DNA gyrase and by generating reactive oxygen species that lead to apoptosis. Proteomes were examined by 2‐D DIGE. Approximately 80 proteins displayed quantitative shifts, 32 showed a correlation with resistance, 24 being linked positively to resistance, 6 correlated negatively. Some known targets did not appear on the 2‐D maps consistently. Keenan, J. et al., Proteomics 2009, 9, 1556‐1566. An image of spit Spitting images have been around for a long time. The phrase is possibly human‐kind's first recognition of genetically transmitted traits. Proteomic analysis of saliva has only developed recently. The question raised by Walz et al. here is “What is the possible contribution of saliva to the high level of infection by Helicobacter pylori?” H. pylori is known to have extracellular adhesins that bind to a number of salivary proteins. A convenient way to detect targets of adhesins was found to be incubating 1‐D and 2‐D PAGE Western blots with an overlay of whole H. pylori. Targets detected included mucins, sialic acid‐containing glycoproteins, fucose‐containing blood group antigens and each pair of salivary glands had a different binding pattern. Walz, A. et al., Proteomics 2009, 9, 1582‐1592. Mix'em up, folks Conventional analytical chemical identifications frequently yield a characteristic spectrum of peaks for particular compounds on particular instruments. Just look up the observed spectrum in the “library” of standard spectra for identification. It is not so simple for proteins. Because of the size of a potential proteomic peptide library and the diversity of instruments used, most often the observed spectrum is compared to a theoretical spectrum for a peptide of interest. Ahrné et al. combine the two for improved performance. First they run the spectrum of interest through an exhaustive proteome search program (Phenyx), then through a sensitive library search (SpectraST) of the highest scoring sequences in the previous Phenyx search plus a number of controls. In the first (relatively simple) test, Phenyx matched 362 spectra, SpectraST made 639 matches at the same error detection level. In a more complex test, Phenyx generated >1000 hits, SpectraST 1304 hits. Ahrné, E. et al., Proteomics 2009, 9, 1731‐1736.     

In this issue: Proteomics 6/2009

In this issue of Proteomics you will find the following highlighted articles: Keeping up with the lung cancers You're in good company if you smoke and develop lung cancer. The World Health Organization estimates 1.2 million new cases occur every year. On the other hand, 1.1 million people die from it every year‐bummer. One reason for the high death rate is the frequent development of resistance to several of the most commonly used drugs simultaneously. Multiple drug resistance (MDR) is the major cause of chemotherapeutic failure. Keenan et al. explored the proteomic changes associated with MDR failure (adriamycin) in a cultured lung cancer cell line (DLKP) and several subtypes. Adriamycin normally kills by blocking replication at DNA gyrase and by generating reactive oxygen species that lead to apoptosis. Proteomes were examined by 2‐D DIGE. Approximately 80 proteins displayed quantitative shifts, 32 showed a correlation with resistance, 24 being linked positively to resistance, 6 correlated negatively. Some known targets did not appear on the 2‐D maps consistently. Keenan, J. et al., Proteomics 2009, 9, 1556‐1566. An image of spit Spitting images have been around for a long time. The phrase is possibly human‐kind's first recognition of genetically transmitted traits. Proteomic analysis of saliva has only developed recently. The question raised by Walz et al. here is “What is the possible contribution of saliva to the high level of infection by Helicobacter pylori?” H. pylori is known to have extracellular adhesins that bind to a number of salivary proteins. A convenient way to detect targets of adhesins was found to be incubating 1‐D and 2‐D PAGE Western blots with an overlay of whole H. pylori. Targets detected included mucins, sialic acid‐containing glycoproteins, fucose‐containing blood group antigens and each pair of salivary glands had a different binding pattern. Walz, A. et al., Proteomics 2009, 9, 1582‐1592. Mix'em up, folks Conventional analytical chemical identifications frequently yield a characteristic spectrum of peaks for particular compounds on particular instruments. Just look up the observed spectrum in the “library” of standard spectra for identification. It is not so simple for proteins. Because of the size of a potential proteomic peptide library and the diversity of instruments used, most often the observed spectrum is compared to a theoretical spectrum for a peptide of interest. Ahrné et al. combine the two for improved performance. First they run the spectrum of interest through an exhaustive proteome search program (Phenyx), then through a sensitive library search (SpectraST) of the highest scoring sequences in the previous Phenyx search plus a number of controls. In the first (relatively simple) test, Phenyx matched 362 spectra, SpectraST made 639 matches at the same error detection level. In a more complex test, Phenyx generated >1000 hits, SpectraST 1304 hits. Ahrné, E. et al., Proteomics 2009, 9, 1731‐1736.     

The hydrological niche and spatially structured species co‐existence

Identifying niche differences and trade‐offs that contribute to species co‐existence in field studies remains a challenge (Hille Ris Lambers et al. 2012, Annual Review of Ecology, Evolution, and Systematics 43 : 227–248). In this issue of the Journal of Vegetation Science, García‐Baquero et al. test whether plant species show spatial segregation along hydrological gradients. By demonstrating the importance of hydrological niches in structuring plant communities, they provide a mechanistic foundation for stronger tests of species co‐existence.     

REPLY TO COMMENT ON THE LIFE CYCLE AND TOXICITY OF PFIESTERIA PISCICIDA REVISITED1

Free‐living, marine dinoflagellates are typified by a well‐defined, haplontic life cycle with relatively few stages. The most unusual departure from this life cycle is one reported for the heterotrophic dinoflagellate Pfiesteria piscicida Steidinger et Burkholder. This species is alleged to have at least 24 life cycle stages including amoebae and a chrysophyte‐like cyst form ( Burkholder et al. 1992 , Burkholder and Glasgow 1997a ) not previously known in free‐living marine dinoflagellates. Litaker et al. (2002) redescribed the life cycle of P. piscicida from single‐cell isolates and found only life cycle stages typical of free‐living marine dinoflagellates. The discrepancy between these observations and the life cycle reported in the literature prompted a rigorous study to resolve the life cycle of P. piscicida. Burkholder and Glasgow (2002) took exception to this study, arguing that Litaker et al. (2002) misunderstood the life cycle of P. piscicida and ignored recent publications. We present a rebuttal of their criticisms and suggest a simple way to resolve the discrepancies in the P. piscicida life cycle.     

Cover Picture: Proteomics 14/2008

In this issue of Proteomics you will find the following highlighted articles: A spoonful of reality helps the errors go down Physicists predict particles from a theory then go hunting for them. To see if they fit the theory, the scientists make measurements of mass, spin, half‐life, charge, symmetry, etc. Life scientists tend to find particles first, then theorize about what they found. Martinez et al. have developed pattern search/match software that is trained on a set of known data (amino acid sequences) to recognize signal sequences that cause cellular enzymes to modify N‐termini of specified cytosolic proteins. Their accuracy rose dramatically when they expanded the amount of training material and segregated it into modules for the various kingdoms (archaea, fungi, plants, animals, eubacteria). Terminal modifications examined included presence or absence of initial methionine, N‐acetylation, N‐myristoylation, and S‐palmitoylation. The particular modification led to varying degrees of internal accumulation. Martinez, A. et al., Proteomics 2008, 8, 2809–2831. Please don't pet the fish Salmon appear to have no fear of jumping several decimeters out of water on their annual upstream migration but they do seem to have a fear of being lifted out of water for a few seconds once a day. Liu et al. looked at the degree of O‐acetylation of serum N‐glycans of Atlantic salmon over a period of 4 weeks. The salmon N‐glycan pattern was similar to the human. Stress was created by holding the fish out of water for 15 seconds daily. Stressed fish showed a reduced level of mono‐O‐acetylated sialic acids. Di‐O‐acetylated species increased, however, over the 4‐week experimental period. The increase in O‐acetylsialic acid is a potential biomarker for long‐term stress in fish. More work is needed to evaluate the extensibility of these findings. Liu, X. et al., Proteomics 2008, 8, 2849–2857. Cattle and ART and proteomics The ART of cattle raising is not learned in a Parson's School of Bovine Design or Parisian cow ecole, it is “Assisted Reproduction Technologies” and is taught in veterinary programs and schools of agriculture. It includes in vitro fertilization (IVF), somatic cell nuclear transfer (SCNT), and multiple ovulation embryo transfer. Expensive procedures requiring specialized training, they are normally applied only to genetically superior breeding stock. Fetal losses are high — 2× to >10× natural fertilization failure rates. Riding et al. used proteomic technology (2‐D DIGE, MALDI‐TOF‐MS/MS) to look for biomarkers in conceptus fluids. In particular, they sought indicators of fetal‐maternal environment status and fetal health at 45 and 90 days post‐conception for IVF and SCNT. Allantoic fluid samples from 45 days showed elevated levels of cathelicidin antimicrobial protein (CAMP) family members (3 of 4 IVF, up ≤100×; 2 of 4 SCNT, up ≤45×; natural, up ≤6×) and several other proteins (PGLYRP, SERPINB1, COLT1). Riding, G. A. et al., Proteomics 2008, 8, 2967–2982.     

In this issue: Proteomics 14/2008

In this issue of Proteomics you will find the following highlighted articles: A spoonful of reality helps the errors go down Physicists predict particles from a theory then go hunting for them. To see if they fit the theory, the scientists make measurements of mass, spin, half‐life, charge, symmetry, etc. Life scientists tend to find particles first, then theorize about what they found. Martinez et al. have developed pattern search/match software that is trained on a set of known data (amino acid sequences) to recognize signal sequences that cause cellular enzymes to modify N‐termini of specified cytosolic proteins. Their accuracy rose dramatically when they expanded the amount of training material and segregated it into modules for the various kingdoms (archaea, fungi, plants, animals, eubacteria). Terminal modifications examined included presence or absence of initial methionine, N‐acetylation, N‐myristoylation, and S‐palmitoylation. The particular modification led to varying degrees of internal accumulation. Martinez, A. et al., Proteomics 2008, 8, 2809–2831. Please don't pet the fish Salmon appear to have no fear of jumping several decimeters out of water on their annual upstream migration but they do seem to have a fear of being lifted out of water for a few seconds once a day. Liu et al. looked at the degree of O‐acetylation of serum N‐glycans of Atlantic salmon over a period of 4 weeks. The salmon N‐glycan pattern was similar to the human. Stress was created by holding the fish out of water for 15 seconds daily. Stressed fish showed a reduced level of mono‐O‐acetylated sialic acids. Di‐O‐acetylated species increased, however, over the 4‐week experimental period. The increase in O‐acetylsialic acid is a potential biomarker for long‐term stress in fish. More work is needed to evaluate the extensibility of these findings. Liu, X. et al., Proteomics 2008, 8, 2849–2857. Cattle and ART and proteomics The ART of cattle raising is not learned in a Parson's School of Bovine Design or Parisian cow ecole, it is “Assisted Reproduction Technologies” and is taught in veterinary programs and schools of agriculture. It includes in vitro fertilization (IVF), somatic cell nuclear transfer (SCNT), and multiple ovulation embryo transfer. Expensive procedures requiring specialized training, they are normally applied only to genetically superior breeding stock. Fetal losses are high — 2× to >10× natural fertilization failure rates. Riding et al. used proteomic technology (2‐D DIGE, MALDI‐TOF‐MS/MS) to look for biomarkers in conceptus fluids. In particular, they sought indicators of fetal‐maternal environment status and fetal health at 45 and 90 days post‐conception for IVF and SCNT. Allantoic fluid samples from 45 days showed elevated levels of cathelicidin antimicrobial protein (CAMP) family members (3 of 4 IVF, up ≤100×; 2 of 4 SCNT, up ≤45×; natural, up ≤6×) and several other proteins (PGLYRP, SERPINB1, COLT1). Riding, G. A. et al., Proteomics 2008, 8, 2967–2982.     

Akt regulates glutamate receptor trafficking and postsynaptic membrane elaboration at the Drosophila neuromuscular junction

The Akt family of serine‐threonine kinases integrates a myriad of signals governing cell proliferation, apoptosis, glucose metabolism, and cytoskeletal organization. Akt affects neuronal morphology and function, influencing dendrite growth and the expression of ion channels. Akt is also an integral element of PI3Kinase‐target of rapamycin (TOR)‐Rheb signaling, a pathway that affects synapse assembly in both vertebrates and Drosophila. Our recent findings demonstrated that disruption of this pathway in Drosophila is responsible for a number of neurodevelopmental deficits that may also affect phenotypes associated with tuberous sclerosis complex, a disorder resulting from mutations compromising the TSC1/TSC2 complex, an inhibitor of TOR (Dimitroff et al., 2012). Therefore, we examined the role of Akt in the assembly and physiological function of the Drosophila neuromuscular junction (NMJ), a glutamatergic synapse that displays developmental and activity‐dependent plasticity. The single Drosophila Akt family member, Akt1 selectively altered the postsynaptic targeting of one glutamate receptor subunit, GluRIIA, and was required for the expansion of a specialized postsynaptic membrane compartment, the subsynaptic reticulum (SSR). Several lines of evidence indicated that Akt1 influences SSR assembly by regulation of Gtaxin, a Drosophila t‐SNARE protein (Gorczyca et al., 2007) in a manner independent of the mislocalization of GluRIIA. Our findings show that Akt1 governs two critical elements of synapse development, neurotransmitter receptor localization, and postsynaptic membrane elaboration. © 2013 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc. Develop Neurobiol 73: 723–743, 2013