Neutrophils represent the first line of defence against aggressions. The programmed death of neutrophils is delayed by pro-inflammatory stimuli to ensure a proper resolution of the inflammation in time and place. The pro-inflammatory stimuli include granulocyte-macrophage colony-stimulating factor (GM-CSF). Recently, we have demonstrated that although neutrophils have an identical spontaneous apoptosis in elderly subjects compared to that in young subjects, the GM-CSF-induced delayed apoptosis is markedly diminished. The present study investigates whether an alteration of the GM-CSF stimulation of MAPKs play a role in the diminished rescue from apoptosis of PMN of elderly subjects.t-test for independent means. Significance was set for p ≤ 0.05 unless stated otherwise.Neutrophils were separated from healthy young and elderly donors satisfying the SENIEUR protocol. Neutrophils were stimulated with GM-CSF and inhibitors of the MAPKinase pathway. Apoptosis commitment, phosphorylation of signaling molecules, caspase-3 activities as well as expression of pro- and anti-apoptotic molecules were performed in this study. Data were analyzed using Student's two-tailed In this paper we present evidence that an alteration in the p42/p44 MAPK activation occurs in PMN of elderly subjects under GM-CSF stimulation and this plays a role in the decreased delay of apoptosis of PMN in elderly. We also show that p38 MAPK does not play a role in GM-CSF delayed apoptosis in PMN of any age-groups, while it participates to the spontaneous apoptosis. Our results also show that the alteration of the p42/p44 MAPK activation contributes to the inability of GM-CSF to decrease the caspase-3 activation in PMN of elderly subjects. Moreover, GM-CSF converts the pro-apoptotic phenotype to an anti-apoptotic phenotype by modulating the bcl-2 family members Bax and Bcl-xL in PMN of young subjects, while this does not occur in PMN of elderly. However, this modulation seems MAPK independent.Our results show that the alteration of p42/p44 MAPK activation contributes to the GM-CSF induced decreased PMN rescue from apoptosis in elderly subjects. The modulation of MAPK activation in PMN of elderly subjects might help to restore the functionality of PMN with aging. Neutrophils represent the first line of defence against aggressions . They arOnce the neutrophils finished their cleaning and modulating role, they should disappear in an ordered manner without releasing toxic products from their granules that eventually harmed the surrounding tissues. If they do not disappear they would induce a chronic inflammatory process. Their elimination for the sake of the organism is occurring through apoptosis -5. Thus,However, in the presence of pro-inflammatory stimuli including lipopolysaccharide (LPS), granulocyte-colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF) neutrophils are able to postpone their spontaneous propensity for dying and thus, remain active during more than 72 hours . This deIt is well accepted that aging is linked to an increase in the susceptibility to various infections . This isThe mechanism of the GM-CSF induced delay of PMN apoptosis is under intense investigation. It is well known that GM-CSF induces three distinct signalling pathways in neutrophils: the Jak/STAT, the MAPK and the PI3K pathways -21. ReceMAPKinases have been shown to have important roles in intracellular mechanisms responsible for neutrophils activation induced by various stimuli, as well as the modulation of their apoptosis ,26-30. TThe present study investigates whether an alteration of the GM-CSF MAPK stimulation play a role in the diminished rescue from apoptosis of PMN of elderly subjects. In the present paper we present evidence that an alteration in the ERK1/2 activation occurs in PMN of elderly subjects under GM-CSF stimulation and this plays a role in the decreased delay of apoptosis of PMN in elderly. We also show that p38 MAPK does not play a role in GM-CSF delayed apoptosis in PMN of any age-groups. Our data also show that the alteration of the p42/p44 MAPK activation results in the inability of GM-CSF to convert the pro-apoptotic phenotype of PMN of elderly subjects to an anti-apoptotic phenotype by modulating the Bcl-2 family members Bax and Bcl-xL as well as the caspase-3.N, N, N', N'-tetraacetic acid (EGTA), aprotinin, sodium orthovanadate (Na3VO4), phenylmethylsulfonyl fluoride (PMSF) and ethylenediaminetetraacetic acid (EDTA) were obtained from Sigma-Aldrich (St Louis, MO). Leupeptin, chymostatin and pepstatin were from Boehringer Mannheim (Mannheim, Germany). Iscove's medium was purchased from Life Technologies (Grand Island, NY). The anti-caspase-3 antibody recognizing the p17 fragment of cleaved caspase-3 was a generous gift of Dr. D. Nicholson . Anti-phosphotyrosine mAb (4G10), anti-Bax and anti-Bcl-xL were purchased from Upstate Biotechnology Inc. (Lake Placid, NY). Polyclonal anti phospho-p42/p44 MAPK (Thr202/Tyr204), anti-p42/p44 MAPK, anti phospho-p38 MAPK (Thr180/Tyr182) and anti-p38 MAPK antibodies were from Santa Cruz (Santa Cruz, CA). The MEK inhibitor PD98059 and p38 inhibitor SB203580 were from Calbiochem. Cell permeable inhibitors of caspase-3 (Z-DEVD-FMK) and caspase-8 (Z-IETD-FMK) were purchased from Bio-Rad Laboratories (Mississauga, ON). Fluorometric caspase-3 substrate (Ac-DEVD-AMC), caspase-3 inhibitor (DEVD-CHO), caspase-8 substrate (Ac-IETD-AMC) and caspase-8 inhibitor (IETD-CHO) were from Biosource International. Propidium iodide was from R&D Systems (Minneapolis, MN). Other reagents were obtained from Sigma-Aldrich unless stated otherwise.Human recombinant GM-CSF was purchased from Calbiochem-Novabiochem (La Jolla, CA). Ethylene glycol-bis (β-aminoethyl ether)-Venous blood was collected from 20 young (20–25 years) and 20 elderly (65–85 years) individuals satisfying the SENIEUR protocol criteria for immunogerontological studies, as described . All sub6 cells/ml) in Iscove's modified Dulbecco's medium supplemented with 10% autologous serum, 50 U/ml penicillin and 25 μg/ml streptomycin and incubated in the presence or absence (control) of GM-CSF, at a concentration of 20 ng/ml which had been previously determined to induce maximal PMN response. Other agents used included: H2O2 (250 μM) and FMLP (10-8 M). These concentrations were previously determined to induce maximal activation (16). The cells were incubated for various periods of time (6 and 18 hours) in polypropylene tubes (Becton Dickinson Labware, Lincoln Park, NJ) at 37°C in a humidified 5% CO2-95% air incubator. For some experiments the MEK1/2 inhibitor, PD98059, and the p38 inhibitor, SB203580, were used at 30 μM and 10 μM, respectively for 1 hour prior to GM-CSF stimulation, as this concentration (from 7,5 to 100 μM) and time point (from 30 to 240 min) had been shown to be the most effective to block these MAPK activities. Stock solution of GM-CSF, H2O2, FMLP, and PD98059 as well as SB203580 were prepared in DMSO . Preliminary experiments showed that these concentrations of DMSO did not increase cell necrosis or the rate of PMN apoptosis.All experiments were performed using media, serum and reagents that were free of endotoxins to avoid non-specific activation of PMN. Purified PMN were suspended (5 × 102, pH 7.4) in 12 × 75 mm polystyrene tubes. FITC-Annexin V at a saturating concentration was added to the cell suspension and incubations were performed in the dark at room temperature for 15 min. Non-specific staining was determined using a Ca2+-free buffer (10 mM HEPES, 140 mM NaCl, 10 mM EDTA, pH 7.4). Fluorescence was filtered through a 530/30 nm band pass to record FITC-Annexin V emission and a 582/42 nm band pass to detect PI emission. Fluorescence intensity was measured on a FACScan flow cytometer (Becton Dickinson, Mountain View, CA) equipped with a 15 mm air cooled 488 nm argon-ion laser. Gating on physical parameters was used to exclude cell debris and clumps. A minimum of 10,000 events was analyzed in each experiment.Apoptosis of PMN was measured by flow cytometry using FITC-conjugated Annexin V to label externalized phosphatidylserine, whereas propidium iodide staining was used to differentiate apoptosis from necrosis . The cel7 cells) were cultured in the absence or presence of GM-CSF (20 ng/ml) and lysed in a buffer containing 20 mM Tris-HCl, pH 7.4, 137 mM NaCl, 10% glycerol, 1% Nonidet P-40, 2 mM sodium vanadate and 100 mM sodium fluoride for a 30 min on ice. Cell lysates were centrifuged at 16,000 × g for 15 min and protein concentration of the supernatants was determined by using the Bradford protein assay reagent (Bio-Rad). 20 μg of cell lysates were resolved on a 8% SDS-PAGE, transferred to Hybond nitrocellulose membranes (Amersham Biosciences) and antigens revealed by probing the membrane with an anti-phosphotyrosine antibody (4G10) or the relevant antibodies p42/p44MAPK and p38MAPK (phosphorylated or not), Bax, Bcl-xL, caspase-3. Membranes were then washed six times with TBS and incubated with horseradish peroxidase-conjugated secondary antibody for 1 h at room temperature. The protein bands were revealed by densitometry analysis was performed using the Chemigenius2 Bio Imaging System (Syngene, Frederick, MD) [PMN (106 cells) were lysed in 100 μl of a 10 mM potassium phosphate, 1 mM EDTA buffer (pH:7.4) containing 0.5% Triton X-100 supplemented with 2 mM PMSF, 10 μg/ml leupeptin, 10 μg/ml pepstatin, and 10 mM dithiotreitol for 15 min on ice and spun at 14,000 rpm for 20 min. The lysate (100 μg) was diluted to 1 ml with ICE buffer (50 mM HEPES, 10% sucrose, 0.1% CHAPS, pH 7.5) containing 50 μM of the caspase-3 substrate Ac-DEVD-AMC  [PMN (5 × 10ate-AMC)  and 10 mate-AMC)  activityt-test for independent means. Significance was set for p ≤ 0.05 unless stated otherwise.Results are representative of experiments performed with 20 individual donors of each age group. Results are presented as pooled data from the entire series of experiments (mean ± SD). Data were analyzed using Student's two-tailed In control neutrophils obtained from young subjects, the mean percentage of apoptotic cells increased steadily from 5 ± 2.7% at 0 hour to 30 ± 6.5% at 18 hours , FMLP and Z-DEVD-FMK, an inhibitor of caspase-3 (iC3) on the modulation of the PMN apoptosis for various periods of time. It is well known that GM-CSF is able to rescue PMN from their spontaneous apoptosis [We evaluated, by the expression of Annexin-V using flow cytometry measurements, the effects of GM-CSF, Hpoptosis . As showPMN of young and elderly subjects were stimulated with GM-CSF during various periods of time . Here we analyzed by western-blotting experiments the amount of activated caspase-3 after different experimental conditions including GM-CSF and inhibitors treatment. We found that after 18 hours, GM-CSF-treated PMN of young subjects reduced significantly the expression of activated caspase-3 as compared to untreated cells (Figure To confirm these results, we measured the caspase-3 activity by a specific fluorescent substrate Table . In PMN To further link the MAPK pathways to survival/apoptosis of PMN we assessed the caspase-3 activity under GM-CSF stimulation after PD98059 and SB203580 pre-treatment. We found that any of these inhibitors alone did not modulate significantly the caspase-3 activity during the spontaneous apoptosis of PMN obtained either from young or elderly subjects (Table Many clinical data indicate that elderly subjects are more susceptible to infections, particularly to that of the higher respiratory tracts, more likely caused by atypical organisms as well as to sepsis by gram negative bacteria ,14. PMN We have found that in PMN of elderly subjects the GM-CSF was not able to rescue them from apoptosis as efficiently as in PMN of young subjects . Here weGM-CSF is activating three signalling pathways, Jak/STAT, MAPK and PI3K . It is nAs the p42/p44 MAPK was implicated in PMN of young subjects in the rescue from apoptosis, we studied whether this could contribute to the failure of rescue with aging. In fact, the activation of this MAPK by GM-CSF, as well as by other substances is strongly related to its anti-apoptotic effect, showed by the use of specific MEK1/2 inhibitors -30. Our We also studied whether another member of the MAPK family namely the p38 MAPK participates to the GM-CSF induced rescue from apoptosis. The role of the p38 MAPK in PMN apoptosis is controversial -36. Neveet al. [Finally to understand how the p42/p44 MAPK can be implicated in the GM-CSF induced apoptosis of PMN we studied molecules intervening in the modulation of PMN apoptosis. These molecules enclosed those of the Bcl-2 family members and the caspases, mainly caspase-3. It was shown that the Bcl-2 family members are either pro-apoptotic or anti-apoptotic. In PMN the most important pro-apoptotic molecule is Bax and the most important anti-apoptotic ones are the Mcl-1, A1 and Bcl-xL . The preFurthermore, we were also interested to study the effects of p42/p44 MAPK on the expression and activity of another very important executioner protein, the caspase-3. Caspase-3 was implicated in the spontaneous and GM-CSF induced rescue of PMN from apoptosis. In fact we confirmed that GM-CSF could decrease the activated caspase-3 expression and activity in PMN of young subjects, while has no effect in PMN of elderly. It was also known that the p42/p44 MAPK is inhibiting the activation of caspase-8 . The useAltogether, our data demonstrate to our best knowledge for the first time that the lack of activation of p42/p44 MAPK contribute to the decreased rescue of PMN from apoptosis in elderly individuals. This decreased activation results in a pro-apoptotic Bcl-2 family members over-expression and the activation of caspase-3 in contrast to PMN of young subjects. We also present data that the activation of p42/p44 MAPK should be sustained for at least 18 hours to ensure an efficient rescue of PMN from apoptosis by GM-CSF. Moreover, our results confirm that the p38 MAPK participates to the spontaneous apoptosis of PMN in both age-groups while it did not participate in the rescue of PMN apoptosis by GM-CSF. Thus, the perspective of modulation of the p42/p44 MAPK activation in PMN of elderly subjects may be useful to restore the effectiveness of GM-CSF and contribute to more effective PMN functionality in elderly. We explore actually what means can be used to achieve such an increase in p42/p44 MAPK activation, including the modification of the PMN membrane composition.


The integration of the rapidly expanding corpus of information about the genome, transcriptome, and proteome, engendered by powerful technological advances, such as microarrays, and the availability of genomic sequence from multiple species, challenges the grasp and comprehension of the scientific community. Despite the existence of text-mining methods that identify biological relationships based on the textual co-occurrence of gene/protein terms or similarities in abstract texts, knowledge of the underlying molecular connections on a large scale, which is prerequisite to understanding novel biological processes, lags far behind the accumulation of data. While computationally efficient, the co-occurrence-based approaches fail to characterize  biological interactions. Programs with natural language processing (NLP) capability have been created to address these limitations, however, they are in general not readily accessible to the public.We present a NLP-based text-mining approach, Chilibot, which constructs content-rich relationship networks among biological concepts, genes, proteins, or drugs. Amongst its features, suggestions for new hypotheses can be generated. Lastly, we provide evidence that the connectivity of molecular networks extracted from the biological literature follows the power-law distribution, indicating scale-free topologies consistent with the results of previous experimental analyses. can be accessed free of charge to academic users.Chilibot distills scientific relationships from knowledge available throughout a wide range of biological domains and presents these in a content-rich graphical format, thus integrating general biomedical knowledge with the specialized knowledge and interests of the user. Chilibot  A comprehensive understanding of the rapidly expanding corpus of information about the genome, transcriptome, and proteome at large scale requires extensive integration with existing knowledge that often pertains to a number of biological disciplines. Despite the existence of specialized databases e.g. ,2), most, most2])chip literature robot), which constructs content-rich relationship networks between genes, proteins, drugs and biological concepts . This is achieved by automatically querying the PubMed literature database and extracting information using natural language processing (NLP) techniques.Chilibot is an Internet-based application . The sysTerms that can be queried include gene symbols, UniGene identifications (including human, rat and mouse) and/or free-form keywords (e.g. "ischemia", "apoptosis", "methylation"). Chilibot retrieves the synonyms of the queried terms from an internal database. The synonym table is compiled from 6 genomic or proteomic databases (see table The texts (including each title and abstract) are then parsed into units of one sentence, which has been shown to yield higher performance levels than paragraphs or phrases in the identification of relationships from MEDLINE abstracts . SentencRetrieved relationships are visualized using AiSee (AbsInt, Angewandte Informatik GmbH, Germany). Nodes (boxes) are used to represent query terms and lines for relationships. Icons with different shapes and colors are added to the middle of each line to indicate the nature of the relationship, with arrows indicating directionality. Color coding of individual nodes can be used to report the magnitude of change in experimental data, when provided by the user; different shades of green or red represent up- or down-regulation, respectively, and more saturated colors are associated with larger changes. The weight of an interactive relationship, reflecting the number of abstracts obtained from PubMed, is displayed within the icon figure. . The co-We used a set of 770 known relationships (see Methods) specified in the Database of Interacting Proteins (DIP)  to measuAmongst the 68 DIP relationships that Chilibot did not detect table , the larTo estimate precision, defined as the fraction of retrieved relationships that are relevant, we randomly selected 100 relationships from the 702 relationships recovered by Chilibot . We manually confirmed that the documentation retrieved by Chilibot contained information about 96 of the targeted relationships, and the remaining four shared symbols with other genes. In the interactive category, directionality was correctly identified in 79.1% and inhibitory/stimulatory properties in 74.4%. The original data used to perform these analyses are available see  and 2.One of the key features of Chilibot is its capacity to link the relationships represented in the network map directly to their supporting documentation, usually as sentences containing both of the query terms. In addition, each node is linked to its synonym list and to a set of statements demonstrating the use of the term; these statements are selected from abstract texts by an algorithm favoring conclusive statements (see Methods). By providing the literature in a condensed and highlighted form, Chilibot facilitates the rapid comprehension of the relationships by the user.Chilibot provides several options for customizing the query process and for viewing the identified relationships. Context specific searches restrict the analysis of relationships to a specific subject area, as defined by the user. Internet searches can also be customized (e.g. searching only documents in PDF format) by using Google WebAPI. Specific subsets of relationships contained in an overall relationship map can be reconfigured. For example, the user can customize the relationship map by requesting only those relationships with direct linkage to a specific node, or those that have a requisite number of supporting publications [see Chilibot also identifies key index terms common to the relationship network. To do so, Chilibot uses Medical Subject Headings (MESH) , a contrChilibot also has the capability of suggesting new hypotheses based on the retrieved network of relationships. Such hypotheses, originally described by Swanson et al. as "undiscovered public knowledge" , referreTo test the value of these "hypothetical relationships" in predicting the results of future research, we queried 22 genes known to be involved in long-term potentiation (LTP), an electrophysiological phenomenon closely associated with memory formation. Chilibot identified a direct relationship between LTP and all 22 genes, along with 194 inter relationships amongst the 22 genes. We then performed retrospective studies by limiting the search to literature published before the years 2000, 1995 and 1990 . It was Based on the literature that is currently available, Chilibot identified new hypothetical relationships, such as those between synaptophysin/CREB and synaptotagmin/CREB. Currently no direct empirical evidence for these relationships is available. However, scanning the 5' untranslated region of the synaptophysin and synaptotagmin genes did show multiple CREB binding sites, providing bioinformatics-based evidence supporting the plausibility of these potential interactions. Although these examples are promising, they are hypothetical relationships. Further review of the scientific literature, such as the sentences provided by Chilibot, is required to clarify the rationale for these hypotheses.Recent large-scale studies of metabolic , transcr2 = 0.76, p < 0.001). This suggests that the discovery of biological relationships attributable to specific nodes might be influenced both by the amount of scientific effort deliberately devoted to understanding that node and the intrinsic connectivity of that node. Although the commitment of greater resources by the scientific community to certain nodes may bias the topology of the scientific literature to some extent, this is likely to be regulated and limited by the strength of the findings, which would be directly related to the intrinsic connectivity of a particular node. Thus, it is reasonable to postulate that the topology of the biomedical literature on gene/protein interactions may reflect that of the interactions per se.For comparison to the preceding biological networks, we studied the connectivity of the literature-based networks obtained by applying Chilibot to three groups of randomly selected genes (300 genes per group). The resulting networks contain 224, 116, and 138 nodes and 3018, 962, and 1912 relationships, respectively. Visualization of the network structure of one of the groups is provided see . The conThe scale-free topology of gene/protein relationships provides another dimension for comparing and prioritizing research targets after large-scale experiments. Currently, genes or proteins with large-fold changes are generally favored for further study . HoweverChilibot graphically summarizes the relationships amongst a large set of user provided terms by analyzing abstracts retrieved from the PubMed literature database. We have found in our benchmark tests that these retrieved relationships are reliable. We believe that the scientific community will benefit from this literature mining capability along with the many features that Chilibot provides, especially in an era of science when insight can be submerged in an overwhelming sea of data and modularized knowledge.Flat text file versions of the six databases (HUGO, LocusLink, OMIM, GDB, SwissProt, and SGD) were downloaded from their corresponding ftp sites. Symbol-name pairs were extracted from the corresponding fields using Perl scripts. Names were curated to remove words that are unlikely to be used in texts, such as "partial cDNA", "fragment", etc. In addition, non-alphanumerical characters were converted into spaces. Entries with the same symbol from the six databases were then combined in a case insensitive manner. The final dictionary is stored in the Postgresql relational database. server. Optimization was necessary because phrase or adjacency searches are not supported by PubMed. Thus, when searching for names with multiple words, it is possible to retrieve abstracts that contain all the relevant words, however the words are used in different places of the abstract. Further, PubMed has an automatic term mapping feature that converts user input according to the MESH translation table. For our purposes, we considered this an undesirable feature. After small scale testing, the query structure we selected places a title and abstract restriction tag ([tiab]) after the name of the query term. This disables the term translation feature and also treats the term as a phrase when possible, according to PubMed documentation. To test the effectiveness of this strategy, we sampled 510 names with lengths ranging from 1 to 11 words. A total of 4584 abstracts were retrieved. We were able to find the query name from 4487 (97.9%) of the abstracts. We thus constructed the pair-wise PubMed query in the following format:The NCBI Eutilies, in particular Esearch and Efetch, are used in conjunction with the Perl LWP module to interact with the (Term 1 synonym 1 [tiab] OR Term 1 synonym 2 [tiab] OR ...) AND (Term 2 synonym 1 [tiab] OR Term 2 synonym 2 [tiab] OR ...)Many methods e.g. -40] have have40]]All the context keywords provided by the user are combined with an "OR" operation. This string is then combined with the pair-wise PubMed queries, using an "AND" operation. The context keywords are not used in subsequent analyses.A synopsis is a collection of sentences used to annotate the query terms. It is generated from the first 100 sentences that contain the specific query term or its synonyms. These sentences are sorted by a weighting mechanism that favors short, conclusive sentences. Words suggesting a conclusion, such as "suggest", "found", "show", "data" etc weights as +9 points. Starting the sentence with the query term and a verb weights as +5 points. The presence of words suggesting a negative result such as "not", "lack", "fail", "without" is weighted as -3 points. Having more than 30 words also reduces the weight by 3 points. Lastly, having keywords specified by the user adds 5 points to the weight. The 15 sentences with the highest weights are displayed.Title and abstract texts retrieved via the Efetch utility are first parsed into individual sentences using a Perl script. Only sentences containing both of the query terms or their synonyms are subjected to NLP analysis, which includes POS tagging by the TnT software  and shalAll sentences containing two query terms (or their synonyms) are classified into one of six categories: stimulatory (interactive), inhibitory (interactive), both stimulatory and inhibitory (interactive), neutral (interactive), parallel (non-interactive) and abstract co-occurrence only. Sentences are classified into interactive or non-interactive relationships based on the presence or absence of a verb phrase between the two query terms. The following exceptions apply: sentences are classified as parallel when the query terms are present in two separate clauses; sentences without a verb phrase between the query terms, but with specific terms indicating interactions such as "interaction", "bind", etc., are classified as interactive; interactive relationships are converted into parallel relationship when there is a negation (such as "not") within the same clause of the verb phrase. The interactive relationship is further classified into stimulatory, inhibitory, or neutral subtypes based on the presence or absence of words describing such relationships, including "activate", "facilitate", "increase", "induce", "stimulate", "enhance", "elevate", "inactivate", "abolish", "attenuate", "block", "decrease", "eliminate", "inhibit", "reduce", "suppress". For interactive relationships, the direction is defined as from the left query term to the right term and is reversed when passive voice is detected. To avoid the influence by spurious mistakes, the overall relationship between two terms is defined as interactive only when more than 20% of the sentences are detected as either stimulatory or inhibitory. Lastly, the co-occurrence type is assigned when the two query terms are located in the same abstract but not the same sentence. We ranked the informativeness of the relationships in the following order: both stimulatory and inhibitory, either stimulatory or inhibitory, neutral interactive, parallel, abstract co-occurrence. The overall relationship between two query terms is classified as the most informative type of relationship.Network layout is generated using the aiSee software. Each pair of query terms identified as having relationships is specified by nodes and represented by square boxes. The relationships are represented by solid lines. A special node with unique identification (an icon) is inserted into the middle of each line. The icon is either circular or rhomboidal depending on the relationship it represents  by the user, Chilibot scans the retrieved network to find those nodes that are not directly linked to NR, but have connections to the same tertiary nodes as NR. Chilibot then produces a new network map for each of these "hypothetical relationships", while maintaining the links to the supporting documentation. To test the usefulness of these "hypothetical relationships" in predicting future research, a total of 22 terms (ACTIN, ACTININ, AMPA, ARC, ATF, CAMKII, CAMKIV, CREB, ERK, KV4.2, NMDA, PI-3K, PKA, PKC, PLC, SYNAPSIN I, SYNAPTOPHYSIN, SYNAPTOTAGMIN, TAU, TRKA, TRKB, AND ZIF268) were queried together with LTP (long-term potentiation). Retrospective studies were performed by querying these terms again while adding the PubMed date limiting tag "&mindate=1960&maxdate=$maxdate", where the $maxdate equals to 1990, 1995, 2000, respectively.The MESH Keywords of the abstracts represented by the graph are collected and sorted by their weighted percentage. When the keyword is the major topic of the publication, it is weighted as 3. Otherwise, it is weighted as 1. The weights are then divided by the number of abstracts to obtain the weighted percentage.Google WebAPI is accessed through Perl scripts. Due to the limitation of the WebAPI, the query terms are searched directly without the expanded synonyms. The URIs of the top 10 hits were retrieved from Google and then the content of these pages was obtained from their individual servers. These pages are then converted into texts, and sentences containing either one of the query terms are presented to the user. Sentences containing both of the query terms are highlighted. Links are also provided to restrict the web search to educational institutions or to files in the portable document format (PDF). Google is a trademark of Google Technology, Inc.DIP  is a curHC conceived of the project (together with BMS), coded the Chilibot program, performed the evaluations and drafted the manuscript. BMS conceived of the project (together with HC), participated in its design, coordination and analysis, and edited and revised the manuscript.All none-graphic files are archived with tar and compressed with bzip2 to reduce file size.A total of 770 known relationships were used to test the recall and precision of Chilibot. A maximum of 5, 10, 20, 30, 40, or 50 most recent PubMed records for each relationship was specified for analysis. The relationships identified by Chilibot are summarized and provided in Microsoft Excel and OpenOffice format.Click here for fileThe original results of the above study .Click here for fileSub-network graph obtained by filtering figure Click here for fileSub-network graph obtained by filtering figure Click here for fileThe original Chilibot query results of the term "long-term potentiation (LTP)" and 22 other terms, limiting the latest references analyzed to the years 1990, 1995, 2000, and 2004.Click here for fileA graph demonstrating the scale-free topology of relationship networks derived from the biological literature. The network contains 138 nodes and 1912 relationships. A small fraction of the nodes (10 nodes colored in black) accounted for more than 45% of the relationships (solid lines), a characteristic of scale-free topology.Click here for file


Bacteria are an indiscriminate lot. While most organisms tend to pass their genes on to the next generation of their species, bacteria often exchange genetic material with totally unrelated species. That is why skeptics doubted that bacteria researchers could ever hope to map a reliable history of cell lineages in bacteria over time. But now, thanks to the availability of sequenced genomes for groups of related bacteria, researchers at the University of Arizona demonstrate that constructing a bacterial family tree is indeed possible.lateral gene transfer, organisms acquire genetic material not from their ancestors, the most prevalent route, but from unrelated organisms. Lateral gene transfer greatly complicates the issue of who descended from whom, because two organisms could appear closely related based on the similarity of some genes but distantly related based on other genes. The problem is to determine which genes have been faithfully vertically transmitted—from parent cell to offspring—and thus reflect the history of the bacterial cell lineages.Previous efforts to trace the ancestry of bacteria were constrained by a dearth of related bacterial genomes, which, among other things, prevented scientists from successfully accounting for bacteria's tendency to exchange genes with unrelated organisms. In this process, called In this issue, Nancy Moran, Emmanuelle Lerat, and Vincent Daubin propose an approach that solves this problem by identifying a set of genes that serve as reliable indicators of the vertical transfer of bacterial cell lineages. This method has important implications for biologists studying the evolutionary history of organisms by establishing a foundation for charting the evolutionary events, such as lateral gene transfer, that shape the structure and substance of genomes. With this method, scientists can begin to understand how bacteria have evolved and how their genomes have changed.Escherichia coli and Salmonella species) with the most documented cases of lateral gene transfer and the highest number of species with sequenced genomes.Bacteria promise to reveal the most information about genomic evolution, because so many clusters of related bacterial genomes have been sequenced—allowing for broad comparative analysis among species—and their genomes are small and relatively compact. In this study, the researchers chose the ancient bacteria group Proteobacteria, an ecologically diverse group  with widespread distribution in the different species of Proteobacteria that could be used to trace the history of the cell lineages. Surprisingly, they found that almost all of the 205 ortholog gene families they selected supported the same evolutionary branching pattern. Only two did not, which the researchers then investigated and found to be the result of lateral gene transfer.These results, the researchers say, support the ability of their method to reconstruct the important evolutionary events affecting genomes. By mapping out the evolutionary path of genetic information on a genomic level, their approach promises to elucidate not only the evolution of bacterial genomes but also the diversification of species.


Iron is necessary for neuronal function but in excess generates neurodegeneration. Although most of the components of the iron homeostasis machinery have been described in neurons, little is known about the particulars of their iron homeostasis. In this work we characterized the response of SH-SY5Y neuroblastoma cells and hippocampal neurons to a model of progressive iron accumulation.We found that iron accumulation killed a large proportion of cells, but a sub-population became resistant to iron. The surviving cells evoked an adaptative response consisting of increased synthesis of the iron-storage protein ferritin and the iron export transporter IREG1, and decreased synthesis of the iron import transporter DMT1. Increased expression of IREG1 was further substantiated by immunocytochemistry and iron efflux experiments. IREG1 expression directly correlated with iron content in SH-SY5Y and hippocampal cells. Similarly, a high correlation was found between IREG1 expression and the rate of iron efflux from SH-SY5Y cells.Neuronal survival of iron accumulation associates with increased expression of the efflux transporter IREG1. Thus, the capacity of neurons to express IREG1 may be one of the clues to iron accumulation survival. Because of its intense oxidative metabolism, the brain consumes a high fraction of total oxygen generating large amounts of reactive oxygen species ,2. AlthoIn vertebrates, cellular iron levels are post-transcriptionally controlled by the activity of iron regulatory proteins (IRP1 and IRP2), cytosolic proteins that bind to structural elements called iron-responsive elements (IREs). IREs are found in the untranslated region of the mRNAs of the major proteins that regulate cellular iron homeostasis: the transferrin receptor, involved in plasma-to-cell iron transport, and the iron-storage protein ferritin. IRP2-/- mice are born normal but in adulthood develop a movement disorder characterized by ataxia, bradykinesia and tremor . IRP1-/-Iron is internalized into cells by the import transporter DMT1. Four DMT1 isoforms have been identified that differ in both the N-and the C-termini . Two of A new iron transporter, IREG1, also known as ferroportin or MTP1, was recently described ,13. The In this study we examined iron homeostasis in SH-SY5Y neuroblastoma cells and hippocampal neurons. We found that iron accumulation killed a large proportion of cells, but a sub-population became resistant to iron accumulation developing an adaptative mechanism intended to decrease intracellular iron content.Iron accumulation was determined in SH-SY5Y cells grown to confluence and then cultured for two days in media containing from 1.5 to 80 μM iron Figure . Total cFerritin, the main iron-storage protein in mammalian cells, is considered the first line of defense against iron overload. Increasing iron from 1.5 to 5 μM produced a robust 4-fold increase in cell ferritin content Figure . FurtherWe further characterized iron homeostasis in SH-SY5Y cells by examining the expression of the iron importer DMT1 Figure . A 3.5-fGiven that the presence of IREG1 in the central nervous system has been   reported [], it wasThe presence of IREG1 in SH-SY5Y neuroblastoma cells and hippocampal neurons was further documented by immunocytochemistry. IREG1 was detected in both types of cells, with a predominantly cytosolic distribution pattern Figure . The levEfflux of iron from neurons has never been reported. In view of the presence of IREG1, we tested whether SH-SY5Y cells actually had an iron efflux function. To that end, iron efflux from cells pre-cultured for 2 days with varied iron concentrations was determined by atomic absorption spectrometry. This method was preferred to the use of radioisotopic iron since the latter could underestimate a putative iron efflux because of isotope dilution with the pre-existing iron pool . The mixture was incubated for 15 min on ice and centrifuged for 10 min at 5,000 × g. Protein concentrations were determined using the bicinchoninic acid (BCA) protein assay. The supernatant was stored at -70°C. For Western analysis, 30 micrograms of protein from each sample were boiled in Laemmli sample buffer for 5 min and subjected to SDS-PAGE on a 7.5% acrylamide gel. Proteins were transferred to nitrocellulose membrane and blocked for 1 hr at 25°C with 5% nonfat dry milk in blocking saline (20 mM Tris, 0.5 M NaCl, 0.05% Tween-20). Membranes were incubated with primary antibody overnight at 4°C, rinsed with blocking saline and incubated with horseradish peroxidase-conjugated anti-rabbit IgG antibody for 1 hr at 25°C. Transferred proteins were detected with a peroxidase-based chemiluminiscence assay kit . Chemiluminiscence was detected using a Molecular Imager FX device (Bio-Rad, Hercules, CA). The bands were quantified by densitometry using the Quantity One (Bio-Rad) software.2 plastic wells and cultured in a 5 % CO2 incubator in MEM/F12 medium supplemented with 10 % fetal bovine serum and 5 mM glutamine. The medium was replaced every two days. Under these conditions, doubling time was about 48 hours. After 8 days in culture, the culture reached a steady-state number of cells. At this time, cells were challenged with iron for the next two days as described [3+ as the complex FeCl3-sodium nitrilotriacetate. Cell viability was quantified by the MTT assay (Molecular Probes, OR) following the manufacturer's instructions. This model of iron loading attempts to replicate neuronal iron accumulation that occurs during life [Human neuroblastoma SH-SY5Y cells (CRL-2266, American Type Culture Collection Rockville, MD), were seeded at 1 × 105 cells in 2-cmescribed . In brie2. Cultures were maintained in 10% bovine serum until 3 hours after plating, when the culture medium was replaced with medium containing B27 supplement [Hippocampal neurons were prepared from E18.5 rat embryos . Neuronspplement . After 36.The intracellular labile or reactive iron pool of neuroblastoma cells was determined as described ,24. The Cells grown in cover slips were sequentially fixed with 2% and 4% parafolmaldehyde (PFA) in Eagles' MEM, and then washed three times with phosphate-buffered saline (PBS). The fixed cells were permeabilized with Triton-X-100 (0.2%) in PBS at room temperature for 3 min and blocked with defatted milk (10%) in PBS for more than 1 h. The cells were incubated with anti-IREG1 antibody (1:500) overnight at 4°C, washed with PBS and then incubated with Alexa-546-conjugated goat anti-rabbit IgG. The labeled cells were observed with a Zeiss LSM 510 Meta confocal laser scanning microscope.Variables were tested in triplicates, and experiments were repeated at least twice. Variability among experiments was <20%. One-way ANOVA was used to test differences in mean values, and Turkey's post-hoc test was used for comparisons (In Stat program from GraphPad Prism). Differences were considered significant if P < 0.05.MTN conceived of the study, participated in its design and coordination and drafted the manuscript. PA performed the experiments with hippocampal neurons, did the ferritin assays and participated in the analysis and interpretation of data. MN optimized the immunocytochemistry detection of IREG1, performed the confocal microscope observations and participated in the analysis and interpretation of data. VT did the Western blot, labile iron pool and viability assays and contributed to the discussion of the results. MA set up the method to determine total Fe concentration, did the sample and control measures of iron and participated in the analysis and interpretation of data. All coauthors participated in refining the text.


SF), for every gene on an array. The SF is obtained from a trimmed average signal of the array after excluding the 2% of the probe sets with the highest and the lowest values.Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The default method in GeneChip expression microarray uses a constant factor, the scaling factor . In comparison with normalization factors obtained from the median signal or from the mean of the log transformed signal, SF showed the greatest variation. The normalization factors obtained from log transformed signals showed least variation.Among the 76 U34A GeneChip experiments, the total signals on each array showed 25.8% variations in terms of the coefficient of variation, although all microarrays were hybridized with the same amount of biotin-labeled cRNA. The 2% of the probe sets with the highest signals that were normally excluded from SF calculation failed to show any benefit. Normalization factors obtained with log transformed signals performed the best. Thus, it is suggested to use the mean of the logarithm transformed data for normalization, rather than the arithmetic mean of signals in GeneChip gene expression microarrays.Eliminating 40% of the signal data during  A single GeneChip® can hold more than 50,000 probe sets for every gene in human genome. A probe set is a collection of probe pairs that interrogates the same sequence, or set of sequences, and typically contains 11 probe pairs of 25-mer oligonucleotides [The high-density oligonucleotide microarray, also known as GeneChipleotides . Each paleotides . Gene exleotides -10. The leotides ,11.The purpose of data normalization is to minimize the effects of experimental and/or technical variations so that meaningful biological comparisons can be made and true biological changes can be found among multiple experiments. Several approaches have been proposed and shown to be effective and beneficial. They were mostly from studies on two-color spotted microarrays -19. SomeSF and/or a normalization factor (NFaffy). When both the SF and NFaffy are equal to 1, there is no normalization or manipulation of original data. Both NFaffy and SF are computed in virtually the same way. NFaffy is calculated in comparison analysis to compare the array average of one experiment with that of a baseline experiment, while SF is obtained from the signal average of one experiment comparing with a common value, the target signal in absolute analysis [The statistical algorithm in current GeneChip software (MAS 5 and GCOS 1) for gene expression microarray data has eliminated the negative gene expression values, a problem present in earlier versions of the software . It usesanalysis -5,11,22.In this report, a total of 76 experiments with rat U34A GeneChip were analyzed. As shown in Table SF calculation can be ignored. However, the sum of the 2% of the probe sets with the highest signals, the TrimTotal as used in this report, was responsible for about 40% of the total signals , but less with medians (R = 0.536) and the mean of log signals (R = 0.643). The trimmed percentage (Tp) was found to be negatively associated with the median (R = 0.558, b = -1.116) and the mean of log signals (R = 0.495, b = -0.968), but not with the total signal of all probe sets.The rat U34A GeneChip contained 8799 probe sets; hence 2% was about 176 probe sets. The sum of the 2% of the probe sets with the lowest signals accounts for less than 0.1% of the total signals (0.05% ± 0.01%, mean ± SD, n = 76) and its impact on NFLogMean showed a higher correlation with NFMedian than with SF. There were larger differences between NFLogMean and SF than those between NFLogMean and NFMedian . The 4% of the probe sets that was removed from NFTrimLogMean calculation reduced the total data by only 4% after log transformation.Among other approaches to global linear normalization, one can also use the median signal or the mean of logarithm transformed signals to calculate the NF. ian Fig. . To testNFs mentioned above was used instead to estimate the 'true' NF. To compare them with the true NF, a score (NFscore) is introduced. Each NF is calculated against the respective 'true' NF to obtain its NFscore. The average NFscore (± SD) is 7.01% (± 6.24%), 4.51% (± 3.48%), 2.25%(± 2.33%) and 1.95% (± 1.61%), and the sum of NFscore is 5.33, 3.43, 1.71 and 1.48 for SF, NFMedian, NFTrimLogMean and NFLogMean, respectively . It is fair to conclude that NFLogMean produced the least variation.Since it is impossible to obtain the true normalization factor, an average of the four global linear SF in absolute analysis (single array) and the NF in comparison analysis (two arrays) [SF had a larger variance than the median-based NF, or the NF based on the mean of log transformed signals. Similar results were observed in other GeneChip expression arrays, such as mouse U74A and human U133A (data not shown). Elimination of the highest and the lowest 2% of the probe set signals did not stabilize the trimmed means. When intra-array variance was reduced by 40%, this approach cannot be considered to be optimal. The logarithmic transformation of signals stabilized the variation well and made the normalization process much less dependent upon the mean and less affected by the outliers.Logarithmic transformation is a well-accepted approach for stabilizing variance and has become a common choice for data transformation and normalization for spotted microarrays ,16. Much arrays) ,7,11,22.Although simple and popular, the global linear normalization has its drawbacks, especially when the relationship among multiple experiments or genes is not linear. To address such problems, several methods have been proposed to conduct local and non-linear normalization, ,20,22,27SF) is calculated from a trimmed average of gene expression level after excluding the 2% of the data points of the highest values and the lowest values. It is shown here that the 2% of the probe sets of the highest signals contained from 34% to 54% of the total signals. Elimination of the outliers did not reduce, but increased the variation among multiple arrays. Instead, normalization factors obtained from the mean of the log transformed signals had the best performance. Thus, the current scaling method, although widely used, is not optimal and needs further improvement. The mean of logarithm transformed signals is highly recommended to use for normalization factor calculation.Normalization of microarray data allows direct comparison of gene expression levels among experiments. A global linear normalization, called scaling has been widely used in GeneChip microarray technology for gene expression analysis. The scaling factor 24-T4 (Genset Corp, La Jolla, CA) and biotinlated UTP and CTP were used to generate biotin labeled cRNA according to the recommended protocols . Rat genSF) is obtained using equation (1) in comparison with a chosen fixed number, called the target signal (TS) and is verified with the results from MAS 5.0 of the same settings [Gene expression data exported from MAS 5.0 were submitted to a Perl script to calculate different normalization factors. In the scaling approach, a trimmed average signal is calculated after excluding 2% probe sets with the highest signals and 2% with the lowest signal values. The scaling factor (settings ,4,11.SFj = TS / STrimMeanj     (1)Other normalization factors for comparison were obtained by the following:NFMedianj = TS / Sj med    (2)NFLogMeanj = 2 nfji = 1..., n represents the probe sets, j = 1..., J represented the array experiments, Si is the signal of the anti-log of a robust average (Tukey biweight) of log(PM-MM) reported from MAS 5.0 [Sj medis the median signal on the array j, STrimMeanj is the trimmed average on array j after excluding 2% of the probe sets with the highest and the lowest signals [NFMedianj is obtained by using the median signal on array j, and NFLogMeanj is obtained by using the mean of log transformed signals. TS was set to 150, 38 and 38 for SF, NFMedian and NFLogMean, respectively in order to have similar NFs.where  signals ,4,11,22.NFscore is introduced. NFscorej = (NFj - TrueNFj)/TrueNFj, and TrueNFj = (SFj + NFMedianj + NFLogMeanj + NFTrimLogMeanj)/4, where NFTrimLogMeanj, was calculated from equation (3) excluding the 2% of the probe sets with the highest and lowest signals, TrueNFj was used as a 'true' NF. Sum of .In comparison with different NFs, a score, TrimTotal is the sum of the signals from the 2% of the probe sets with the highest signal values. Total signal Total is the sum of the signals of all probe sets in the array, and trimmed percentage Tpj =  × 100%.Unless otherwise specified, logarithm transformation is carried out with the logarithm base 2. Trimmed total signal ® is the registered trademark owned by Affymetrix Inc.GeneChipPM: perfect Match; MM: mismatch; SF: scaling factor; NF: normalization factor; TS: target signal Short phrase: Normalization of GeneChip microarray data


In order for the immune system to generate its vast numbers of receptors, B- and T-cell receptor genes are created by recombining preexisting gene segments. This well- coordinated set of reactions is explained RAG1 and RAG2). The segments are then reassembled using a common cellular repair mechanism.The immune system needs to be able to identify and ultimately destroy foreign invaders. To do so, it utilizes two major types of immune cells, T cells and B cells (or, collectively, lymphocytes). Lymphocytes display a large variety of cell surface receptors that can recognize and respond to an unlimited number of pathogens, a feature that is the hallmark of the “adaptive” immune system. To react to such a variety of invaders, the immune system needs to generate vast numbers of receptors. If the number of different types of receptors present on lymphocytes were encoded by individual genes, the entire human genome would have to be devoted to lymphocyte receptors. To establish the necessary level of diversity, B- and T-cell receptor (BCR and TCR, respectively) genes are created by recombining preexisting gene segments. Thus, different combinations of a finite set of gene segments give rise to receptors that can recognize unlimited numbers of foreign invaders. This is accomplished by a supremely well-coordinated set of reactions, starting with cleaving DNA within specific, well-conserved recombination signal sequences (RSSs). This highly regulated step is carried out by the lymphocyte-specific recombinationactivating genes (For foreign invaders and their proteins (antigens) that are not part of the host to elicit an immune response, the immune system must be able to recognize countless numbers of antigens. For obvious reasons, an unlimited number of unique antigen receptors cannot be genetically encoded. Rather, the necessary diversity in receptors is achieved by creating variations in the antigen-recognition regions of the receptors of both B cells and T cells. These regions are created by the pairing of two different protein segments, called polypeptide chains (heavy [H] and light [L] chains in the case of the BCR and α and β chains in the case of the TCR), which form a cleft that provides a binding site for the antigen. The mechanism that generates variation in the antigen-binding pockets of these receptors involves mixing and matching variable (V), diversity (D), and joining (J) gene segments in a process called V(D)J recombination. To assemble a single functional receptor, preexisting V, D, and J gene segments are rearranged to yield a contiguous V(D)J region, just upstream of another element of the receptor, the constant (C) region .The BCR H chain and the TCR β chain consist of V, D, and J segments, while BCR L chains and the TCR α chain are comprised of only V and J segments. The number of each type of segments within the chains allows for a large but finite combinatorial possibility in rearrangement, a phenomenon termed combinatorial diversity . HoweverRAG1 and RAG2) work together to recognize and bind RSSs. The complex consisting of these two proteins, RAG1–RAG2 (henceforth RAG), cuts the DNA between the rearranging DNA segments and the adjacent RSS motifs (In the first part of the “cut-and-paste” reaction, breaks within both strands of the DNA helix (double-stranded breaks) are made within the RSS sites; in the second part, the newly created breaks are repaired by the cell's general DNA repair pathway. In the initial phase, two lymphocyte-specific proteins that are encoded by the recombinationactivating genes (S motifs . The secS motifs . Both paRAG genes have been deleted (RAG−/−), V(D)J recombination is completely abolished, and these mice have neither mature B nor T cells (RAG genes (RAG proteins carry out the first enzymatic step of the reaction—site-specific cleavage of DNA . Artific T cells . A similAG genes .In test-tube experiments, purified RAG proteins are sufficient for cleavage of a synthetic DNA containing the appropriate RSS . This reRSSs are found next to every variable (V), diversity (D), and joining (J) segment. They consist of three distinct elements: a heptamer and a nonamer sequence, separated by a spacer element—either 12 or 23 bp long  Tonegaw. AlthougPLoS Biology by Both the heptamer and the nonamer contain nucleotides that are absolutely required for efficient V(D)J recombination. The first three nucleotides within the heptamer are conserved, whereas mutations in the next four positions affect but do not abolish the reaction. Within the nonamer, positions 5 and 6 are conserved, while variations are tolerated elsewhere in the sequence . The lenAfter RAG cuts the DNA at the RSS, the two sides of the break are different. The coding ends are closed to resemble hairpins, while the RSS ends are open and blunt. These blunt RSS ends are rejoined rapidly, forming SJs, but before the coding ends can be fused, the hairpins must be opened .Normally, hairpins are opened either at the tip or on the side. In either case, an enzyme called terminal deoxynucleotidyl transferase can add a small amount of random (nontemplated) nucleotides to freed ends, and this phenomenon of N-nucleotide addition contributes to junctional diversity of the CJs .When the hairpin is opened on the side, the reaction leaves a short overhang on one strand. When the overhangs are filled, palindromic sequences are generated, and these modifications are referred to as “P-nucleotides” . These, RAG−/− mice do not have mature B and T cells. This causes a severe combined immunodeficiency syndrome (SCID) characterized by a complete block in B- and T-cell development, but no other defects (As mentioned,  defects . However defects . Mice de defects . These m defects . Hence,  defects .RAG genes on, investigators have suspected that V(D)J recombination may be the result of the landing of a transposable genetic element (a “jumping gene” or transposon) into the vertebrate genome. The clues were many. Firstly, the compact organization of the RAG locus resembles a transposable element J recombination is absolutely crucial for the adaptive immune response. In its absence, our immune system is compromised. When it is not properly controlled, it gives rise to chromosomal translocations and B-and T-cell cancers. The elucidation of all steps of the reaction and attempts to understand exactly how these steps are regulated to avoid disastrous side effects are areas of study that have occupied researchers in the past and will continue to do so in the future.


The importance of AREs in biology is that they make certain mRNA unstable. Proto-oncogene, such as c-fos, c-myc, and c-jun in humans, are associated with AREs. Although it has been known that the increased number of ARE motifs caused the decrease of the half-life of mRNA containing ARE repeats, the exact mechanism is as of yet unknown. We analyzed the occurrences of AREs and Alu and propose a possible mechanism for how human mRNA could acquire and keep AREs at its 3' UTR originating from Alu repeats.A significant portion (about 8% in the human genome) of mammalian mRNA sequences contains AU (Adenine and Uracil) rich elements or AREs at their 3' untranslated regions (UTR). These mRNA sequences are usually stable. However, an increasing number of observations have been made of unstable species, possibly depending on certain elements such as Alu repeats. ARE motifs are repeats of the tetramer AUUU and a monomer A at the end of the repeats ((AUUU)Interspersed in the human genome, Alu repeats occupy 5% of the 3' UTR of mRNA sequences. Alu has poly-adenine (poly-A) regions at its end, which lead to poly-thymine (poly-T) regions at the end of its complementary Alu. It has been found that AREs are present at the poly-T regions. From the 3' UTR of the NCBI's reference mRNA sequence database, we found nearly 40% (38.5%) of ARE (Class I) were associated with Alu sequences Table  within oAREs are mediating sequence elements affecting the stabilization or degradation of mRNA at the 3' untranslated regions. However, AREs' mechanism and origins are unknown. We report that Alu is a source of ARE. We found that half of the longest AREs were derived from the poly-T regions of the complementary Alu. For example, the mRNA sequences of yeast, many mammalians, and other eukaryotes contain AU-rich elements or AREs at their 3' untranslated regions (UTR) [nA motif, is the well-known pattern of AREs. It has been shown that the number of ARE motifs correlated with the turnover of ARE-mRNAs such as GM-CSF [Varying more than ten-fold, messenger RNA degradation is essential for the regulation of gene expression ,2. Diffens (UTR) . For exans (UTR) ,6. Genesns (UTR) -9. The ls GM-CSF ,11. Becas GM-CSF .It is known that the stabilization factor, such as HuD, is able to bind to AREs  and mostAREs consist of a great number of thymine (or uracil) and a few adenines. Alu repeats can be a source of poly-T regions in mRNA. Therefore, there is a possible link between ARE and Alu repeats.Alu repeats are sequences of approximately 300 nucleotides (nt) transcribed by RNA polymerase III. The Alu region is then reverse-transcribed and inserted into a new location in the genome . It can We investigated the link between Alu sequence and the potential AREs , and suggest that the complementary poly-adenine regions of Alu is one of the sources of AREs at the 3' UTR of mRNA. Figure The results from the method are shown in Figure The possible mechanism of how AREs originated from Alu is as follows: Alu is a special sequence that contains a poly-adenine (poly-A) region at its end. The poly-A region plays an important role in the retroposition mechanism of Alu . It is kWith this hypothesis, we suggest a new role for Alu was involved in the 3' UTR. It is well known that Alu affected gene expression at the 5' of genes and alternative splicing at the intron region ,39. HoweAREs are mediating sequences that affect the stabilization or degradation of biologically important genes' mRNA. However, their origin in evolution has not been clear. This report presents a hypothesis and statistical evidence that Alu was one of the sources of ARE generation or origin. A possible mechanism of ARE generation from Alu via retroposition and regular pattern mutation is suggested.We used the RefSeq database from the National Center for Biotechnology Information (NCBI) for human 3' UTR sequences . We extrAREs were searched for in the all 3' UTR Table . An in-hWe compared the positions of 3' UTR Alu and ARE sequences. If an ARE was discovered within an Alu sequence, this ARE was regarded found in 3' UTR Alu. For example, if an Alu was found between 100–400 bp and an ARE was found between 99–129 bp, this ARE was in 3' UTR Alu in the same 3' UTR. If less than 50% of an ARE length was discovered in an Alu, we further check if there is 7 bp TSD (Target Site Duplication) between the Alu's end and the ARE's end [To validate the significance of the searches, we calculated the random chance of the ARE and Alu sequence overlap at each class Table .H0: ARE occurs in human 3'UTR independently from Alu.The average length of 3' UTR of 21,121 human sequences was 996 bp. Within the long theoretical sequence of 21,121 × 996 bp, we generated 1,504 Alu (300 bp) and ARE sequences (21–13 bp). For example, 1,504 Alu and 26 (21 bp) AREs in ARE class I (Table In the ARE class I Table , the sigHJA conceived of this study, carried out the tests, and drafted the manuscript. JB participated in the design of the study and drafted the manuscript. KWL and DL amended and improved the design of the study. All authors read and approved the final manuscript.


Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files; however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags ("quasi-ditags").We provide examples of quasi-ditags that originate from cloning and sequencing artifacts (i.e. genomic contamination or random combinations of nucleotides) that are included in SAGE libraries. We have employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences, and our data show that clones containing less than or equal to 2 ditags  should be excluded from the analysis of SAGE catalogs.Cloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data. Serial Analysis of Gene Expression (SAGE) is a rapid method to study mRNA transcripts in cell populations . Two majNlaIII or Sau3A  as anchoring enzymes (AE) to create SAGE tags. Both of these enzymes have 4-bp palindromic recognition sequences (CATG for NlaIII and GATC for Sau3A) that flank individual ditags within concatemers. A major component of the software analysis is the identification of anchoring enzyme recognition sequences (AERS) that flank target sequences (SAGE ditags). After finding the first AE recognition sequence, the software continues reading the sequence until it finds the next one. The software then compares the distance between these recognition sequences with predicted ditag lengths (20–24 bp in the case of NlaIII or Sau3A), and ditags that are too short (<20 bp) or too long (>24 bp) are excluded. However, if the length of the AERS-flanked sequence satisfies the size criteria, it is identified as a ditag. This algorithm relies on the assumption that all sequences have correctly organized ditag concatemers; however, the cloning efficiency of SAGE rarely reaches 100%. In this report, we show that up to 5% of ditags from some SAGE libraries should be omitted from the final analysis. These false ditags (termed "quasi-ditags") result from genomic contaminants and apparently random combinations of nucleotides generated by cloning or sequencing errors. Using a mathematical model to simulate the frequency of quasi-ditags in DNA, we propose a method to exclude quasi-ditags from SAGE catalogs.SAGE data are usually analyzed with software packages like "SAGE300" or "SAGE2000". The majority of SAGE libraries use From twelve independent SAGE libraries, we analyzed numerous clones lacking organized ditag concatemers that would be excluded by SAGE software packages, including clones lacking inserts, clones with inserts containing bacterial or rodent genomic sequences, and clones with unidentifiable sequences Figure . DependiDuring our sequence analysis of the clones that had produced a least number of ditags (1–2 per clone), we identified a subset of sequences (up to 40%) that contain ditags that may be false. Importantly, some of these "ditags" matched bacterial genomic sequences Figure , while oSaccharomyces cerevisiae genomic DNA that lack SAGE ditag concatemers was also employed for in vivo / in silico model validation, and a number of quasi-ditags was detected in these . At the same time, the frequency of occurrence for three quasi-ditags (3Q) is extremely low (0.01% for L = 600 to 0.02% for L = 1200), such that the value of P3 (20–24) effectively converges to zero for the majority of the SAGE catalogs (i.e. <3000–5000 clones) , large-scale amplifications of this plasmid within bacteria would be expected to lead to some random recombinations, and the generation of quasi-ditags  of various origins. Although SAGE software packages are designed to ignore sequences that lack 20–24 bp sequences flanked by two anchoring enzyme recognition sites, it does not exclude quasi-ditags originating from genomic contaminants or unknown sequences that may arise as cloning or sequencing artifacts  do not match genomic sequences and thus might be originated from sequencing errors. We therefore suggested a model that provides a mathematical basis for the hypothesis that such a possibility exists. The mathematical model presented in the manuscript is an attempt to predict the frequency distribution of quasi-ditags in random sequences. The phenomenon itself is rather complex and there is no simple model that would capture it in full complexity. We, however, believe that we have selected a reasonable level of model complexity that captures the major pattern of frequency distribution.in silico experiments show that the probability of finding more than two quasi-ditags in the same sequence converges effectively to zero ), suggests that single or double ditags may represent quasi-ditags; however, the results of the –6), suggro Table . Based oChart in Figure Comparing values of observed frequencies of the actual SAGE clones that produce 1–2 total ditags with those of expected quasi-ditag frequencies for the sequences of given length might be indicative on the possible contribution of cloning and sequencing artifact-derived quasi-ditags Figure . The posSAGE protocols are extremely complex technologically and every possible mean should be employed to ensure qualitative and quantitative accuracy of catalogs on both the experimental and analytical steps. Evaluation of the cloning efficiency and precision (e.g. with RAST-PCR ) and seqWe have hypothesized that actual SAGE catalogs could be contaminated by false ditags (termed "quasi-ditags") of various origins and employed a mathematical model to predict the frequency of quasi-ditags in random nucleotide sequences. Cloning and sequencing artifacts contaminating SAGE libraries could be eliminated using simple pre-screening procedure to increase the reliability of the data.NlaIII and BsmFI restriction enzymes (New England Biolabs, Beverly, MA, USA). Sequencing was performed by Perkin-Elmer Applied Biosystems / Celera Genomics (Foster City, CA, USA) and Agencourt Bioscience Corporation (Beverly, MA, USA).Serial analysis of gene expression (SAGE) was performed according to the original protocol  with min-4 = 1/256. In a sequence of length L, the expected number of AERS (e.g. CATG for NlaIII anchoring enzyme) is L/256. Thus, the probability of finding k tags CATG in a random sequence of length L is determined by the Poisson distribution:Anchoring enzyme recognition sites (AERS) are 4 bp long. Assuming for simplicity that all 4 nucleotide bases (A, T, C, and G) have equal frequencies, a probability that a random combination of 4 nucleotides would match the AERS is 4(CATG)) are located within the sequence of length L, then the probability that they are separated by a 20–24 bp distance (P(20–24)) is approximately:If two CATG sequences (AERS(CATG) that yield a quasi-ditag and 24 is the mean distance from the center of one SAGE tag to the end of the sequence that does not leave enough space for another tag to form a quasi-ditag.where 10 is the number of possible relative positions of two AERSIf >2 AERS are present in the sequence, then there is a chance that additional AERS would appear within the quasi-ditag formed by first two AERS. A probability that additional AERS will not appear within the quasi-ditag is approximately:where 30 is the average length of a nucleotide string outside of the ditag.(CATG) equals k, then the number of possible AERS pairs is:If the total number of AERSk AERS(CATG) is:Taken together, a probability of at least one quasi-ditag in the sequence that has exactly Q1) to find at least one quasi-ditag in a sequence of given length L is:Then, a probability (where p(k) is given by equation (1).(CATG) could serve as a portion of the two neighboring quasi-ditags (...CATG-(N)20–24-CATG-(N)20–24-CATG...). In other cases, two or more quasi-ditags can be located independently in the sequence. If a sequence with k tags already has one quasi-ditag bounded by two tags, then other (k-2) tags may form additional quasi-ditags. The probability of existence of additional quasi-ditags on condition that one ditag is already present is approximately q(k-2). Then the total probability that any random sequence has at least two quasi-ditags is:There is also a probability that more than one quasi-ditag exists within the sequence. In some cases the same AERSIn the same way,and so on.The probability that a random sequence has exactly n quasi-ditags is:Rn = Q(n) - Q(n + 1)     (9).Saccharomyces cerevisiae that lack SAGE ditag concatemers were also employed for in vivo / in silico model validation. Randomly selected S. cerevisiae chromosomes were downloaded from GenBank, fragmented to create a minimum of 300 sequences (L = 600–1200) and searched for quasi-ditags using "SAGE2000" software (available at SAGE website [A random nucleotide generator (for L = 600–1200) and analysis program that mimics "SAGE300" or "SAGE2000" software algorithms was written in Visual Basic and is available upon request. Genomic DNA sequences of  website ). FrequeSVA developed the hypothesis, overall plan and performed SAGE, computer simulations, and analysis of Yeast genome fragments. AAS developed and implemented the mathematical model predicting the appearance of "quasi-ditags" in random sequences of given length. Both authors have contributed to the writing and approved the final manuscript.


II and p30II whose roles are beginning to be defined in the virus life cycle. Previous studies indicate the importance of these viral proteins in the ability of the virus to maintain viral loads and persist in an animal model of HTLV-1 infection. Intriguing new studies indicate that p30II is a multifunctional regulator that differentially modulates CREB and Tax-responsive element-mediated transcription through its interaction with CREB-binding protein (CBP)/p300 and specifically binds and represses tax/rex mRNA nuclear export. A new study characterized the role of p30II in regulation of cellular gene expression using comprehensive human gene arrays. Interestingly, p30II is an overall repressor of cellular gene expression, while selectively favoring the expression of regulatory gene pathways important to T lymphocytes. These new findings suggest that HTLV-1, which is associated with lymphoproliferative diseases, uses p30II to selectively repress cellular and viral gene expression to favor the survival of cellular targets ultimately resulting in leukemogenesis.Human T-lymphotropic virus type-1 (HTLV-1) is a complex retrovirus that causes adult T-cell leukemia/lymphoma (ATL) and is implicated in a variety of lymphocyte-mediated disorders. HTLV-1 pX ORF II encodes two proteins, p13 Both HTLV-1 pX ORF I and II mRNAs have been detected in infected cell lines and blood leukocytes from HTLV-1-infected subjects including ATL and HAM/TSP patients [The complex sequence of events set in motion by human T-lymphotropic virus type 1 (HTLV-1) to cause proliferation and ultimately transformation of T lymphocytes is beginning to be unraveled. Only recently has it become clear that viral encoded proteins, the so-called "accessory" gene products of this complex retrovirus, play an integral role in the pathogenic process. In addition to the structural and enzymatic gene products, HTLV-1 encodes regulatory and accessory proteins from four open reading frames (ORF) in the pX region between provirus . The welprovirus . Tax orcprovirus ,6. Recenprovirus -9. Althopatients ,11. Alsopatients -14.I and p13II/p30II in the establishment of infection and maintenance of viral loads in a rabbit model of infection [II has minimal homology to transcription factors Oct-1 and -2, Pit-1, and POU-M1 [II and HTLV-2 p28II(homologous protein encoded in the HTLV-2 pX ORF II region), in repressing the export of tax/rex mRNA from the nucleus [Molecular clones of HTLV-1 with selective mutations of ORF I and II have revealed the requirement of p12nfection -17. The d POU-M1 -21. In ad POU-M1 . Intrigu nucleus ,24. ThusII as a regulator of gene expression in Jurkat T cells. They identified alterations in gene expression profiles unique to cell cycle regulation, apoptosis, and T lymphocyte signaling/activation. Although p30II expression, as might be expected from earlier reports, resulted in a general repressive pattern of gene expression, their data indicated that the viral protein selectively spared or enhanced NFAT, NFκB, and AP-1 mediated transcription in T cells undergoing co-stimulation. Signaling pathways primarily affected by p30II as measured by luciferase reporters included both NFAT and NFκB, which increased from approximately 3 to 11 fold, depending on co-stimulatory treatment. Overall, this study supports earlier reports on the repressive role of HTLV-1 p30II in gene expression [II may play a role in HTLV-1 replication  declare that they have no competing interests.


Depression is frequently occurring during and after psychosis. The aim of this study was to analyze if the psychosocial characteristics associated with depression/depressive symptoms in the late phase of a first episode psychosis (FEP) population were different compared to persons from the general population.A questionnaire was sent out to all individuals six years after their FEP and to a general population sample. Depressive symptoms were recorded using a self-rating scale, the Major Depression Inventory.Formerly FEP persons had a higher representation of depressive symptoms/depression, unemployment, financial problems and insufficient social network. Depressive symptoms/depression were found to be associated with psychosocial problems. An age and gender effect was found in the general population, but not in the FEP sample. When the psychosocial characteristics were taken into account there were no association between having had FEP and depressive symptoms.The association between having been a FEP patient and depressive symptoms/depression disappeared when negative social aspects were taken into account. Major Depression is the one of the most common psychiatric disorders and is frequently occurring in persons with psychotic disorders. Up to 25% of individuals with psychosis have this condition at some point during the course of their illness .Insufficient social network, unemployment, living alone, financial problems and low social class are among the reported risk factors for depression in prospective studies -5. Studith edition of the Present State Examination and the reliability has been reported to be good [The most commonly used depression self-rating scales in population studies were developed before the introduction of DSM-III, e.g. the Beck Depression Inventory (BDI) and the Zung Self-rating Depression Scale (Zung-SDS) ,12. The  be good . The aut be good .The aim of the present study was to analyze if the psychosocial characteristics associated with depressive symptoms in persons six year after a first episode of psychosis (FEP) differed from the associations found in a population sample.The Parachute project is a Swedish multi center study of FEP. It includes all persons from the catchment area who for the first time sought psychiatric help for psychotic symptoms during 1996–1997. Persons who were 18–45 years old and without a dominating substance abuse or diagnosed brain disorder were included in the study. The catchment area covers approximately 20% of the Swedish population. The project integrates an epidemiological approach with intensive psychosocial and medical treatment of a cohort of first episode psychotic patients. It includes a large-scale system of "need adapted treatment" [Of the 175 patients included in the project from the start 133 were followed during the complete six-year period. The questionnaire included in this study was sent out to the 133 persons six years after their first psychotic episode and 57.1% (76 persons) participated. Those who participated did not differ in age, gender, country of origin or psychiatric diagnosis from those who did not participate.The PART study is a longitudinal population study of risk factors and social consequences of mental ill health in the Stockholm County. 19 744 Swedish citizens aged 20–64 years registered as living in the county of Stockholm were randomly selected in 1998–2000. This represents 1.8% of the population in this age group in this area. 10 442 persons (53%) participated in the study. The personal identification number  of participants as well as non-participants were linked to the following official registers: income and wealth, sick leave, hospital discharge register (including diagnoses) and disability pension. Participation was related to female gender, higher age, higher income and education, being born in Sweden, and having no psychiatric diagnoses in the hospital discharge register or in the disability pension register. The odds ratios for associations between gender, income, country of origin, education and having a psychiatric diagnosis previously according to the registers, were similar among participants and non-participants . Participants having had a diagnosis of psychotic disorder in the hospital discharge register were excluded from this study (n = 20).A questionnaire was sent out to the population included in the PART study. The questions included risk and protective factors for mental illness as well as psychiatric symptoms scales . The sam• Demographic characteristics: age, gender and country of origin (Sweden/other).• Financial problems included the availability to get 14 000 SEK (1 797 USD) within a week, if necessary.• Working life: The persons were divided in the following two groups: employed/students and unemployed/disability pension/sick leave/early retirement pension.• Social network: An instrument developed by Unden & Orth-Gomer  was used• Depressive symptoms: The Major depression Inventory was used strictly according to the authors of the scale ,14. The Simple factorial ANOVA'S were performed using being in the PART population or not as the dependent variable and age, gender and country of origin as covariates. Pearson's correlation was used to see if the demographic and psychosocial variables correlated with depressive symptoms. These analyses were performed separately in the PART and FEP populations. Additionally multiple regression analyses were performed with the scores on the Major Depression Inventory and a cut off score of 26 or more as the dependent variables. All variables were entered simultaneously. Being in the PART population or not was entered as a variable.The demographic and psychosocial characteristics of the two populations are presented and compared in table When using a MDI cut-off score of 26, 25.8% (17 persons) had a score above the cut-off in the FEP population and 8.0% (783 persons) in the general population sample.Table Separate multiple regression analyses were performed in the two samples with the Major Depression Inventory total score as the dependent variable. In the general population sample the adjusted R square was 0.21 (SE 8.7) and in the FEP population 0.28 (SE 11.4). In addition an analysis was made were general population/FEP population was inserted as a variable. The result is presented in table The main finding of this study was that the association between having suffered a FEP and self-reported depressive symptoms/depression six years later disappeared when a negative social situation was taken into account.Not surprisingly, persons with a previous FEP had a higher representation of unemployment, financial problems and insufficient social network, which have been reported in other studies -26. In tThe non-participation rate was high in the general population and persons with severe psychiatric disorders most likely did not respond to the enquiry. However, the associations between gender, income, country of origin, education and having a previous psychiatric diagnosis was similar among participants and non-participants. The FEP group also had a high non-participation rate, although the distribution of age, gender, country of origin and psychiatric diagnoses were similar among participants and non-participants. The general population sample was an urban population while the FEP population was from areas all over Sweden, which might have affected the result.17 and Zung-SDS [The strengths of the study were that the FEP group was a total population, followed over six years and having received treatment according to a "need-adapted approach". Moreover, the instrument in use, the MDI has been reported to have a higher internal validity than Ham-DZung-SDS ,14. The Zung-SDS .The results of this study fully agree with the goals of WHO : Links nHaving had a first episode psychosis six years earlier had no association with depressive symptoms/depression when a negative social situation was taken into account.The authors declare that they have no competing interests.YF, SL and JC participated in the data collection. YF performed the statistical analysis. All three authors wrote and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Streptococcus thermophilus strains will provide a key tool to facilitate the genetic manipulation of this important dairy species.Lactic acid bacteria (LAB) are essential for the manufacture of fermented dairy products. Studies on the physiology, biochemistry and genetics of these microorganisms over the last century have contributed considerably to the improvement of fermentation processes and have resulted in better and safer products. Nevertheless, the potential of LAB is far from being maximized. The sophistication of biotechnologies and the availability of complete genome sequences have opened the door to the metabolic engineering of LAB. In this regard, the recent publication of the complete genome sequences of two  The souring of milk by microorganisms has been used for thousand of years as a natural preservation procedure . The metThe discovery and characterization of lactic acid bacteria (LAB) has tremendously modified the way fermented milk products are made. Considerable efforts have been devoted over the last fifty years to increase our knowledge about the genetics, biochemistry, and physiology of LAB. In addition to enhancing our understanding of microbial life, these studies have allowed dairy microbiologists and cheesemakers to select better strains and improve the productivity, quality, and safety of the final products. The characterization of LAB has promoted the rational development of blends of defined bacterial strains, now known as starter cultures, which are increasingly replacing the undefined blends traditionally used by the dairy industry. This strategy makes it easier to control acid production and, to some extent, phage problems. Unfortunately, it is also widely perceived that this approach reduces the much sought-after rich, complex flavour of fermented products made with undefined cultures. Thus, the search for LAB strains that produce characteristic aroma and flavours remains an attractive challenge for the dairy industry.The increasing awareness of the population of the importance of a healthy diet has led scientists to revisit the century-old hypothesis that some specific fermented dairy products may provide health benefits. A plethora of studies are underway to evaluate this concept and to improve the health benefits of LAB. Also, the long history of the safe use of these bacteria has made them very attractive candidates as vaccine delivery vehicles ,3. LastlLactococcus lactis. The publication of the complete genome sequence of L. lactis in 2001 [L. lactis via genetic manipulation [L. lactis.To meet some of these challenges and promises, it became apparent that metabolic engineering was the best approach. Owing to the industrial interest, the sound knowledge of its genetic and the availability of genetic tools, metabolic engineering of LAB has been carried out mainly with  in 2001  was a bopulation ,6 is a cpulation -12 proviStreptococcus thermophilus strains were published [S. thermophilus is a thermophilic LAB species widely used for the manufacture of yogurt and cheeses that require elevated cooking temperatures such as Swiss and Italian types. The availability of these genome sequences will make it possible to apply genomic-related analytic methods such as functional and comparative genomics, microarray technologies, proteomics, and bioinformatics to this species. These genomic-based technologies will undoubtedly accelerate the metabolic engineering of S. thermophilus, which is still at its infancy. We will briefly discuss current studies that will greatly benefit from these S. thermophilus genomic sequences: food-grade vectors, optimization of lactose metabolism and exopolysaccharide (EPS) production, and resistance to bacteriophages.Recently, the complete genome sequence of two ublished  and a thublished . S. therS. thermophilus strains[Metabolic engineering often involves inactivation or overexpression of relevant chromosomal genes or stringent control of an extrachromosomal foreign gene borne by a plasmid artificially introduced into the host. Plasmids thus play a central role in these studies because they are the primary vehicles used to manipulate target DNA sequences. However, these extrachromosomal genetic elements are naturally but infrequently observed in s strains.S. thermophilus, an efficient, stable, food grade expression system is still lacking. The recent discovery of a novel theta-type replicating plasmid [S. thermophilus, such as galactokinase [S. thermophilus genome sequences also provide crucial information on transcription and translation initiation signals and the codon usage of this bacterium. This may help in the design of efficient expression systems.Understandably, very few cloning tools are at hand, and those that are available are based on similar replication machinery. This lack of diversity poses significant problems for many genetic studies. While several types of transformation methods have been developed to introduce foreign DNA into  plasmid  as well tokinase  and alphtokinase , suggestS. thermophilus to rapidly take up and metabolize lactose is crucial in several fermentation processes. While S. thermophilus readily metabolizes the glucose moiety of lactose, it is unable to metabolize galactose, which is expelled into the external medium. The presence of galactose in yogurt and other dairy products might be unwanted for different reasons. Notably, galactose is poorly metabolized by humans and may cause, under certain conditions, health problems [S. thermophilus results either from poor expression of the gal operon [galK gene coding for galactokinase [galK translation was first suggested by a comparative analysis of the S. thermophilus gal-lac operons with the homologous genes from the phylogenetically related oral bacterium Streptococcus salivarius. This is a convincing example of how comparative genome analysis may help to decipher specific metabolic pathways of LAB. While the introduction of a functional extrachromosomal S. salivarius galK allele in S. thermophilus allows it to grow on galactose, it does not prevent the expulsion of galactose during growth on lactose [S. thermophilus genes are not functional (pseudogenes) and that one third of these pseudogenes are dedicated to sugar metabolism [S. salivarius genome would be welcome since many S. thermophilus pseudogenes involved in sugar transport are functional in S. salivarius [The ability of problems ,19. The l operon  or inefftokinase ,21. The  lactose . In thistabolism . It woullivarius .S. thermophilus are widely used for the commercial manufacture of yogurt because they produce exopolysaccharides (EPS), which give a viscous texture to the fermented dairy product. Other EPS-producing S. thermophilus strains can also enhance the functional properties of some cheeses such as Mozzarella. The organoleptic properties of these products are largely due to the amount and types of exopolysaccharide produced during the fermentation process. The yield and sugar constituents of EPS are influenced by several factors and vary from strain to strain [S. thermophilus does not naturally produce large amounts of EPS, which explains why considerable efforts are being directed toward understanding the cellular mechanisms of EPS biosynthesis. Since low levels of sugar precursors may limit EPS synthesis, a better understanding of S. thermophilus metabolic flux during sugar metabolism may lead to new strategies to enhance EPS production [S. thermophilus by metabolic engineering of central carbon metabolism. Moreover, because EPS yields are growth associated, efforts to increase production levels are likely to require novel strategies to enhance biomass production. This task clearly requires a comprehensive view of the cell machinery. The sequencing of a whole genome is a mandatory step to achieve this goal. As our knowledge of S. thermophilus continues to improve, novel EPS and/or applications for EPS+ cultures are likely to emerge.Some strains of o strain . S. theroduction . Levandeoduction  showed tS. thermophilus hosts should provide new insights in several areas of phage research.Bacteriophages are the most significant cause of fermentation failures in the dairy industry worldwide. Dairy microbiologists have attempted for more than 70 years to eliminate, or at least bring under better control, the bacteriophages that interfere with the manufacture of many fermented milk products . The pubS. thermophilus mutants is generally the first approach used to transform a phage-sensitive strain into a phage-resistant mutant, most likely following spontaneous chromosomal mutation in the gene encoding the phage receptor. Although progress has been made in identifying phage proteins involved in S. thermophilus host recognition [The development of bacteriophage-insensitive ognition , the ideognition , a numbeS. thermophilus phage genomes are now available [S. thermophilus phages are already available[At least eight complete vailable ,28. Phagavailable, meaningS. thermophilus genome sequences will obviously facilitate our understanding of the metabolic potential of S. thermophilus. It will also make it easier to design rational genetic manipulations of this important dairy bacterium in order to produce added value cheeses and yogurts and to use it as a cell factory. In addition, knowing the complete genome sequences should lead to the development of new genetic tools that will provide insights into the evolution of microbial communities, shifts in metabolism, and how each member adapts to the environmental changes that occur during complex fermentation processes.A thorough understanding of LAB metabolism and how it is regulated by external stimuli is a prerequisite for maximizing the potential of LAB. The availability of complete S. thermophilus genome sequence have opened up exciting, new possibilities that will build on an already rich heritage.The exciting biotechnological developments in LAB and studies that are already underway will benefit both consumers and the dairy industry. The availability of the complete