Greater Transport Efficiencies of the Membrane Fatty Acid Transporters FAT/CD36 and FATP4 Compared with FABPpm and FATP1 and Differential Effects on Fatty Acid Esterification and Oxidation in Rat Skeletal Muscle

In selected mammalian tissues, long chain fatty acid transporters (FABPpm, FAT/CD36, FATP1, and FATP4) are co-expressed. There is controversy as to whether they all function as membrane-bound transporters and whether they channel fatty acids to oxidation and/or esterification. Among skeletal muscles, the protein expression of FABPpm, FAT/CD36, and FATP4, but not FATP1, correlated highly with the capacities for oxidative metabolism (r ≥ 0.94), fatty acid oxidation (r ≥ 0.88), and triacylglycerol esterification (r ≥ 0.87). We overexpressed independently FABPpm, FAT/CD36, FATP1, and FATP4, within a normal physiologic range, in rat skeletal muscle, to determine the effects on fatty acid transport and metabolism. Independent overexpression of each fatty acid transporter occurred without altering either the expression or plasmalemmal content of other fatty acid transporters. All transporters increased fatty acid transport, but FAT/CD36 and FATP4 were 2.3- and 1.7-fold more effective than FABPpm and FATP1, respectively. Fatty acid transporters failed to alter the rates of fatty acid esterification into triacylglycerols. In contrast, all transporters increased the rates of long chain fatty acid oxidation, but the effects of FABPpm and FAT/CD36 were 3-fold greater than for FATP1 and FATP4. Thus, fatty acid transporters exhibit different capacities for fatty acid transport and metabolism. In vivo, FAT/CD36 and FATP4 are the most effective fatty acid transporters, whereas FABPpm and FAT/CD36 are key for stimulating fatty acid oxidation.Uptake of long chain fatty acids across the plasma membrane had long been considered to occur via passive diffusion. However, in recent years, there has been a fundamental shift in our understanding, and it is now widely recognized that long chain fatty acids cross the plasma membrane via a protein-mediated mechanism (for reviews, see Refs. 1–3). A number of fatty acid transporters have been identified, including fatty acid translocase/CD36 (FAT/CD36), plasma membrane-associated fatty acid binding proteins (FABPpm), and a family of fatty acid transport proteins (FATP1–6)⁵ (for reviews, see Refs. 1 and 4). Selected stimuli (muscle contraction, insulin, and AICAR) induce the translocation of selected fatty acid transporters (FABPpm, FAT/CD36, and FATP1) from an intracellular depot to the plasma membrane, in both heart and skeletal muscle, resulting in concurrently increased rates of fatty acid transport (for a review, see Ref. 1). Some fatty acid transporters have now also been implicated in the dysregulation of fatty acid metabolism in heart and skeletal muscle in models of insulin resistance and type 1 and 2 diabetes, including FAT/CD36 (5–9), FATP1 (10, 11), and possibly FATP4 (11, 12) but not FABPpm (5–7). Thus, in recent years, it has become widely accepted that (a) long chain fatty acids traverse the plasma membrane via a protein-mediated mechanism and (b) some of the fatty acid transporters are central to the dysregulation in skeletal muscle fatty acid metabolism in obesity and type 2 diabetes.In vivo, many of the fatty acid transporters are frequently co-expressed in different tissues. FAT/CD36 and FABPpm are ubiquitously expressed (1), whereas FATP1–6 exhibit a somewhat tissue-specific distribution pattern (13, 14). The reason for the co-expression of different fatty acid transporters within the same tissue remains unclear. It has been speculated that selected fatty acid transporters may need to interact with each other (15, 16). Alternatively, it is also possible that (a) different fatty acid transporters have discrepant transport capacities, and (b) selected transporters may channel fatty acids differentially to fatty acid oxidation and esterification into triacylglycerols in mammalian tissue.Recent evidence has shown that the transport capacities among FATPs can differ substantially, as revealed by overexpression (14, 17, 18) or knockdown studies (19), but there is little agreement as to which FATP is most effective. Extensive studies by DiRusso et al. (17) in yeast revealed that when FATP1–6 were overexpressed to similar levels (qualitative assessment), FATP4 exhibited 1.7- and 3-fold greater fatty acid transport effectiveness compared with FATP1 and FATP2, respectively, whereas no fatty acid transport capacities were attributable to FATP3, -5, and -6 (17). In contrast, in HEK293 cells, the FATP6 transport capacity was 3- and 6.5-fold greater than FATP1 and FATP4, respectively (14), whereas in 3T3-L1 adipocytes, a fatty acid transport role was evident only for FATP1 and not FATP4 (19). Others have also questioned the transport role of FATP4 (20). These discrepant findings with respect to the transport effectiveness of FATPs may reflect, in part, the use of diverse cell types with ill defined metabolic needs and/or machinery for fatty acid uptake and metabolism. Indeed, several recent reports indicate that fatty acid transport cannot be adequately examined in some cells, because these appear to lack accessory proteins that may be involved in fatty acid transport (21, 22). In addition, extrapolation of results from cultured cells to metabolically important tissue in vivo may also be problematic, since cells and mammalian tissues probably have different requirements for fatty acid utilization, and their regulation of fatty acid uptake may also differ. For example, the mechanisms regulating the acute contraction-induced up-regulation of fatty acid transport and oxidation, such as occurs in heart and skeletal muscle, is probably absent in selected cell cultures.Assessment of fatty acid transporter effectiveness, in vivo, cannot be determined in knock-out animals, since compensatory responses in some fatty acid transporters (FATP1 and -4) occur when another fatty acid transporter (FAT/CD36) has been ablated (23, 24). Thus, the relative effectiveness of selected fatty acid transporters on fatty acid transport in vivo remains unknown. In addition, whether fatty acid transporters channel fatty acids to a particular metabolic fate, as has been suggested based on studies in cultured cells (18, 19, 25), may depend on the cell type being examined.It is desirable to discern the effectiveness of selected fatty acid transporters in mammalian tissues that have a well known system for transporting and utilizing fatty acids and in which fatty acid transporters can be independently up-regulated without disturbing the expression of other fatty acid transporters. These criteria can be satisfied in rat skeletal muscle in which genes can be up-regulated under controlled conditions within a physiologically meaningful range (26–28). Therefore, in the present study, we have compared the independent transport effectiveness of fatty acid transporters (FABPpm, FAT/CD36, FATP1, and FATP4) in skeletal muscle, without disturbing the expression and plasmalemmal content of other fatty acid transporters. In addition, we also examined the contributions of these transporters to fatty acid oxidation and esterification into triacylglycerols. These are the first studies to reveal that in vivo (a) the fatty acid transport effectiveness of fatty acid transporters differs considerably, and (b) in skeletal muscle, these transporters serve to channel fatty acids to oxidation, not esterification into triacylglycerols.     

Splitting the BLOSUM Score into Numbers of Biological Significance

Mathematical tools developed in the context of Shannon information theory were used to analyze the meaning of the BLOSUM score, which was split into three components termed as the BLOSUM spectrum (or BLOSpectrum). These relate respectively to the sequence convergence (the stochastic similarity of the two protein sequences), to the background frequency divergence (typicality of the amino acid probability distribution in each sequence), and to the target frequency divergence (compliance of the amino acid variations between the two sequences to the protein model implicit in the BLOCKS database). This treatment sharpens the protein sequence comparison, providing a rationale for the biological significance of the obtained score, and helps to identify weakly related sequences. Moreover, the BLOSpectrum can guide the choice of the most appropriate scoring matrix, tailoring it to the evolutionary divergence associated with the two sequences, or indicate if a compositionally adjusted matrix could perform better.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29]     

Analysis of Free Energy Signals Arising from Nucleotide Hybridization Between rRNA and mRNA Sequences during Translation in Eubacteria

A decoding algorithm is tested that mechanistically models the progressive alignments that arise as the mRNA moves past the rRNA tail during translation elongation. Each of these alignments provides an opportunity for hybridization between the single-stranded, -terminal nucleotides of the 16S rRNA and the spatially accessible window of mRNA sequence, from which a free energy value can be calculated. Using this algorithm we show that a periodic, energetic pattern of frequency 1/3 is revealed. This periodic signal exists in the majority of coding regions of eubacterial genes, but not in the non-coding regions encoding the 16S and 23S rRNAs. Signal analysis reveals that the population of coding regions of each bacterial species has a mean phase that is correlated in a statistically significant way with species () content. These results suggest that the periodic signal could function as a synchronization signal for the maintenance of reading frame and that codon usage provides a mechanism for manipulation of signal phase.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Arachidonic Acid Stimulates Cell Adhesion through a Novel p38 MAPK-RhoA Signaling Pathway That Involves Heat Shock Protein 27

Rho GTPases are critical components of cellular signal transduction pathways. Both hyperactivity and overexpression of these proteins have been observed in human cancers and have been implicated as important factors in metastasis. We previously showed that dietary n-6 fatty acids increase cancer cell adhesion to extracellular matrix proteins, such as type IV collagen. Here we report that in MDA-MB-435 human melanoma cells, arachidonic acid activates RhoA, and inhibition of RhoA signaling with either C3 exoenzyme or dominant negative Rho blocked arachidonic acid-induced cell adhesion. Inhibition of the Rho kinase (ROCK) with either small molecule inhibitors or ROCK II-specific small interfering RNA (siRNA) blocked the fatty acid-induced adhesion. However, unlike other systems, inhibition of ROCK did not block the activation of p38 mitogen-activated protein kinase (MAPK); instead, Rho activation depended on p38 MAPK activity and the presence of heat shock protein 27 (HSP27), which is phosphorylated downstream of p38 after arachidonic acid treatment. HSP27 associated with p115RhoGEF in fatty acid-treated cells, and this association was blocked when p38 was inhibited. Furthermore, siRNA knockdown of HSP27 blocked the fatty acid-stimulated Rho activity. Expression of dominant negative p115-RhoGEF or p115RhoGEF-specific siRNA inhibited both RhoA activation and adhesion on type IV collagen, whereas a constitutively active p115RhoGEF restored the arachidonic acid stimulation in cells in which the p38 MAPK had been inhibited. These data suggest that n-6 dietary fatty acids stimulate a set of interactions that regulates cell adhesion through RhoA and ROCK II via a p38 MAPK-dependent association of HSP27 and p115RhoGEF.The ability of tumor cells to metastasize to secondary sites is a hallmark of neoplastic disease. Unfortunately, this propensity to spread is the primary cause of morbidity and death in cancer patients (1). Metastasis is clearly a highly regulated, multistep process that occurs in a spatiotemporal manner (2–4). To escape the restrictive compartment boundaries characteristic of adult tissue, separate intravasation and extravasation steps requiring alterations in co-adhesion, adhesion, invasion, and migration must occur. Execution of these biological processes, involving multiple proteins and cellular organelles, require highly coordinated cell signaling mechanisms.The Rho family of small GTPases regulates many facets of cytoskeletal rearrangements that facilitate cell attachment and migration (5–7). Rho GTPases act as molecular switches by changing from an inactive GDP-bound conformation to an active GTP-bound conformation, thereby regulating a signaling pathway. These proteins are directly regulated by Rho guanine nucleotide exchange factors (GEFs),² Rho GTPase activating proteins, and Rho GDP-dissociation inhibitors (8–12). RhoGEFs bind to the GTPase to catalyze the dissociation of GDP, allowing the binding of GTP and thereby promoting Rho activation (8). The RGS (regulators of G protein signaling) domain-containing RhoGEFs are a recently described family of GEFs. Currently, there are three members of this family, PDZ-RhoGEF, LARG, and p115RhoGEF (13–15), in which the RGS domains function as a heterotrimeric GTPase-activating domain (13, 15, 16). The RGS family of RhoGEFs has been shown to regulate Rho during several processes including cytoskeletal rearrangements, cell adhesion, and cancer progression (17–21).There is significant interplay between the activity of small GTPases and signaling derived from fatty acid metabolism (22–28). Linoleic acid, which is metabolized to arachidonic acid, is an n-6 polyunsaturated fatty acid that is present at high levels in most western diets (29). In animal models, diets high in n-6 polyunsaturated fatty acids have been shown to enhance tumor progression and metastasis (30, 31). Additionally, arachidonic acid is stored in cell membranes and is made available by phospholipases under conditions of increased inflammatory response (32). Arachidonic acid is further metabolized by cyclooxygenases (COX), lipoxygenases (LOX), and cytochrome P450 monooxygenases to yield bioactive products that have myriad effects on cells, and altered metabolism of arachidonic acid by COX, LOX, and P450 has been implicated in cancer progression (31, 33–36).We have studied mechanisms of cell adhesion using the MDA-MB-435 cells as a model of a highly metastatic human cancer cell line (37). These cells have been extensively studied for their ability to recapitulate the metastatic cascade in vivo and in vitro, although recent work indicates that the cells currently in use are most likely a human melanoma line (38). We initially observed that arachidonic acid (AA) enhanced adhesion of MDA-MB-435 cells to type IV collagen through specific integrin-mediated pathways (37). Exogenous AA led to the activation of mitogen-activated protein kinase (MAPK)-activated protein kinase 2 and the phosphorylation of heat shock protein 27 (HSP27) via a p38 MAPK-dependent process (39). Inhibition of p38 MAPK activation blocked cell adhesion as did function-blocking antibodies specific for subunits of the collagen receptor (40). More recently, we identified the key metabolite of AA (15-(S)- hydroxyeicosatetraenoic acid) and the upstream kinases (TAK1 and MKK6) that are responsible for activation of p38 MAPK in this system (41).In this study we investigated the role of Rho activation in the MDA-MB-435 cells after exposure to arachidonic acid. Several aspects of the regulation of Rho signaling in these cells provide insights into the cross-talk between important signaling pathways.     

Algorithms for Finding Small Attractors in Boolean Networks

A Boolean network is a model used to study the interactions between different genes in genetic regulatory networks. In this paper, we present several algorithms using gene ordering and feedback vertex sets to identify singleton attractors and small attractors in Boolean networks. We analyze the average case time complexities of some of the proposed algorithms. For instance, it is shown that the outdegree-based ordering algorithm for finding singleton attractors works in time for , which is much faster than the naive time algorithm, where is the number of genes and is the maximum indegree. We performed extensive computational experiments on these algorithms, which resulted in good agreement with theoretical results. In contrast, we give a simple and complete proof for showing that finding an attractor with the shortest period is NP-hard.[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32]     

Aldo-keto Reductase Family 1 Member B10 Promotes Cell Survival by Regulating Lipid Synthesis and Eliminating Carbonyls

Aldo-keto reductase family 1 member B10 (AKR1B10) is primarily expressed in the normal human colon and small intestine but overexpressed in liver and lung cancer. Our previous studies have shown that AKR1B10 mediates the ubiquitin-dependent degradation of acetyl-CoA carboxylase-α. In this study, we demonstrate that AKR1B10 is critical to cell survival. In human colon carcinoma cells (HCT-8) and lung carcinoma cells (NCI-H460), small-interfering RNA-induced AKR1B10 silencing resulted in caspase-3-mediated apoptosis. In these cells, the total and subspecies of cellular lipids, particularly of phospholipids, were decreased by more than 50%, concomitant with 2–3-fold increase in reactive oxygen species, mitochondrial cytochrome c efflux, and caspase-3 cleavage. AKR1B10 silencing also increased the levels of α,β-unsaturated carbonyls, leading to the 2–3-fold increase of cellular lipid peroxides. Supplementing the HCT-8 cells with palmitic acid (80 μm), the end product of fatty acid synthesis, partially rescued the apoptosis induced by AKR1B10 silencing, whereas exposing the HCT-8 cells to epalrestat, an AKR1B10 inhibitor, led to more than 2-fold elevation of the intracellular lipid peroxides, resulting in apoptosis. These data suggest that AKR1B10 affects cell survival through modulating lipid synthesis, mitochondrial function, and oxidative status, as well as carbonyl levels, being an important cell survival protein.Aldo-keto reductase family 1 member B10 (AKR1B10,² also designated aldose reductase-like-1, ARL-1) is primarily expressed in the human colon, small intestine, and adrenal gland, with a low level in the liver (1–3). However, this protein is overexpressed in hepatocellular carcinoma, cervical cancer, lung squamous cell carcinoma, and lung adenocarcinoma in smokers, being a potential diagnostic and/or prognostic marker (1, 2, 4–6).The biological function of AKR1B10 in the intestine and adrenal gland, as well as its role in tumor development and progression, remains unclear. AKR1B10 is a monomeric enzyme that efficiently catalyzes the reduction to corresponding alcohols of a range of aromatic and aliphatic aldehydes and ketones, including highly electrophilic α,β-unsaturated carbonyls and antitumor drugs containing carbonyl groups, with NADPH as a co-enzyme (1, 7–12). The electrophilic carbonyls are constantly produced by lipid peroxidation, particularly in oxidative conditions, and are highly cytotoxic; through interaction with proteins, peptides, and DNA, the carbonyls cause protein dysfunction and DNA damage (breaks and mutations), resulting in mutagenesis, carcinogenesis, or apoptosis (10, 13–19). AKR1B10 also shows strong enzymatic activity toward all-trans-retinal, 9-cis-retinal, and 13-cis-retinal, reducing them to the corresponding retinols, which may regulate the intracellular retinoic acid, a signaling molecule modulating cell proliferation and differentiation (6, 20–23). In lung cancer, AKR1B10 expression is correlated with the patient smoking history and activates procarcinogens in cigarette smoke, such as polycyclic aromatic hydrocarbons, thus involved in lung tumorigenesis (24–26).Recent studies have shown that in breast cancer cells, AKR1B10 associates with acetyl-CoA carboxylase-α (ACCA) and blocks its ubiquitination and proteasome degradation (27). ACCA is a rate-limiting enzyme of de novo synthesis of long chain fatty acids, catalyzing the ATP-dependent carboxylation of acetyl-CoA to form malonyl-CoA (28). Long chain fatty acids are the building blocks of biomembranes and the precursor of lipid second messengers, playing a critical role in cell growth and proliferation (29, 30). Therefore, ACCA activity is tightly regulated by both metabolite-mediated allosteric mechanisms and phosphorylation-dependent mechanisms; the latter are controlled by multiple hormones, such as insulin, glucagon, and growth factors (31–33). ACCA activity is also regulated through physical protein-protein interaction. For instance, breast cancer 1 (BRCA1) protein associates with the ACCA and blocks its Ser⁷⁹ residue from dephosphorylation (34, 35). The AKR1B10-mediated regulation on ACCA stability represents a novel regulatory mechanism, and this current study elucidated the biological significance of this regulation. The results show that AKR1B10 promotes cell survival via modulating lipid synthesis, mitochondrial function and oxidative stress, and carbonyl levels.     

High-definition De Novo Sequencing of Crustacean Hyperglycemic Hormone (CHH)-family Neuropeptides

A complete understanding of the biological functions of large signaling peptides (>4 kDa) requires comprehensive characterization of their amino acid sequences and post-translational modifications, which presents significant analytical challenges. In the past decade, there has been great success with mass spectrometry-based de novo sequencing of small neuropeptides. However, these approaches are less applicable to larger neuropeptides because of the inefficient fragmentation of peptides larger than 4 kDa and their lower endogenous abundance. The conventional proteomics approach focuses on large-scale determination of protein identities via database searching, lacking the ability for in-depth elucidation of individual amino acid residues. Here, we present a multifaceted MS approach for identification and characterization of large crustacean hyperglycemic hormone (CHH)-family neuropeptides, a class of peptide hormones that play central roles in the regulation of many important physiological processes of crustaceans. Six crustacean CHH-family neuropeptides (8–9.5 kDa), including two novel peptides with extensive disulfide linkages and PTMs, were fully sequenced without reference to genomic databases. High-definition de novo sequencing was achieved by a combination of bottom-up, off-line top-down, and on-line top-down tandem MS methods. Statistical evaluation indicated that these methods provided complementary information for sequence interpretation and increased the local identification confidence of each amino acid. Further investigations by MALDI imaging MS mapped the spatial distribution and colocalization patterns of various CHH-family neuropeptides in the neuroendocrine organs, revealing that two CHH-subfamilies are involved in distinct signaling pathways.Neuropeptides and hormones comprise a diverse class of signaling molecules involved in numerous essential physiological processes, including analgesia, reward, food intake, learning and memory (1). Disorders of the neurosecretory and neuroendocrine systems influence many pathological processes. For example, obesity results from failure of energy homeostasis in association with endocrine alterations (2, 3). Previous work from our lab used crustaceans as model organisms found that multiple neuropeptides were implicated in control of food intake, including RFamides, tachykinin related peptides, RYamides, and pyrokinins (4–6).Crustacean hyperglycemic hormone (CHH)¹ family neuropeptides play a central role in energy homeostasis of crustaceans (7–17). Hyperglycemic response of the CHHs was first reported after injection of crude eyestalk extract in crustaceans. Based on their preprohormone organization, the CHH family can be grouped into two sub-families: subfamily-I containing CHH, and subfamily-II containing molt-inhibiting hormone (MIH) and mandibular organ-inhibiting hormone (MOIH). The preprohormones of the subfamily-I have a CHH precursor related peptide (CPRP) that is cleaved off during processing; and preprohormones of the subfamily-II lack the CPRP (9). Uncovering their physiological functions will provide new insights into neuroendocrine regulation of energy homeostasis.Characterization of CHH-family neuropeptides is challenging. They are comprised of more than 70 amino acids and often contain multiple post-translational modifications (PTMs) and complex disulfide bridge connections (7). In addition, physiological concentrations of these peptide hormones are typically below picomolar level, and most crustacean species do not have available genome and proteome databases to assist MS-based sequencing.MS-based neuropeptidomics provides a powerful tool for rapid discovery and analysis of a large number of endogenous peptides from the brain and the central nervous system. Our group and others have greatly expanded the peptidomes of many model organisms (3, 18–33). For example, we have discovered more than 200 neuropeptides with several neuropeptide families consisting of as many as 20–40 members in a simple crustacean model system (5, 6, 25–31, 34). However, a majority of these neuropeptides are small peptides with 5–15 amino acid residues long, leaving a gap of identifying larger signaling peptides from organisms without sequenced genome. The observed lack of larger size peptide hormones can be attributed to the lack of effective de novo sequencing strategies for neuropeptides larger than 4 kDa, which are inherently more difficult to fragment using conventional techniques (34–37). Although classical proteomics studies examine larger proteins, these tools are limited to identification based on database searching with one or more peptides matching without complete amino acid sequence coverage (36, 38).Large populations of neuropeptides from 4–10 kDa exist in the nervous systems of both vertebrates and invertebrates (9, 39, 40). Understanding their functional roles requires sufficient molecular knowledge and a unique analytical approach. Therefore, developing effective and reliable methods for de novo sequencing of large neuropeptides at the individual amino acid residue level is an urgent gap to fill in neurobiology. In this study, we present a multifaceted MS strategy aimed at high-definition de novo sequencing and comprehensive characterization of the CHH-family neuropeptides in crustacean central nervous system. The high-definition de novo sequencing was achieved by a combination of three methods: (1) enzymatic digestion and LC-tandem mass spectrometry (MS/MS) bottom-up analysis to generate detailed sequences of proteolytic peptides; (2) off-line LC fractionation and subsequent top-down MS/MS to obtain high-quality fragmentation maps of intact peptides; and (3) on-line LC coupled to top-down MS/MS to allow rapid sequence analysis of low abundance peptides. Combining the three methods overcomes the limitations of each, and thus offers complementary and high-confidence determination of amino acid residues. We report the complete sequence analysis of six CHH-family neuropeptides including the discovery of two novel peptides. With the accurate molecular information, MALDI imaging and ion mobility MS were conducted for the first time to explore their anatomical distribution and biochemical properties.