- Open Access
Proteomic analysis of the Plasmodium male gamete reveals the key role for glycolysis in flagellar motility
- Arthur M Talman1, 2Email author,
- Judith H Prieto3, 4,
- Sara Marques1,
- Ceereena Ubaida-Mohien5,
- Mara Lawniczak1,
- Mark N Wass6, 7,
- Tao Xu3, 8,
- Roland Frank9,
- Andrea Ecker1,
- Rebecca S Stanway1, 10,
- Sanjeev Krishna11,
- Michael JE Sternberg6,
- Georges K Christophides1,
- David R Graham5,
- Rhoel R Dinglasan12,
- John R YatesIII3 and
- Robert E Sinden1
© Talman et al.; licensee BioMed Central Ltd. 2014
Received: 11 June 2014
Accepted: 28 July 2014
Published: 13 August 2014
Gametogenesis and fertilization play crucial roles in malaria transmission. While male gametes are thought to be amongst the simplest eukaryotic cells and are proven targets of transmission blocking immunity, little is known about their molecular organization. For example, the pathway of energy metabolism that power motility, a feature that facilitates gamete encounter and fertilization, is unknown.
Plasmodium berghei microgametes were purified and analysed by whole-cell proteomic analysis for the first time. Data are available via ProteomeXchange with identifier PXD001163.
615 proteins were recovered, they included all male gamete proteins described thus far. Amongst them were the 11 enzymes of the glycolytic pathway. The hexose transporter was localized to the gamete plasma membrane and it was shown that microgamete motility can be suppressed effectively by inhibitors of this transporter and of the glycolytic pathway.
This study describes the first whole-cell proteomic analysis of the malaria male gamete. It identifies glycolysis as the likely exclusive source of energy for flagellar beat, and provides new insights in original features of Plasmodium flagellar organization.
Development of the haploid malarial parasite in the vertebrate host culminates with formation, in the blood of developmentally arrested sexual forms, the gametocytes. Transmission to the invertebrate vector requires these cells to undergo gametogenesis and fertilization within the blood meal of the engorged female mosquito.
Male gametes of Plasmodium are one of the simplest of all eukaryotic cells. They are composed of very few recognizable cellular entities, among which are a nucleus containing a condensed haploid genome, an axoneme attached to a modified basal body, and a plasma membrane .
The very short life span of the male gamete (30–40 min)  can be divided into different phases. The first is exflagellation, which consists in the budding of eight male gametes from each parental cell. Exflagellation requires vigorous flagellar beating, both to complete cytokinesis and to liberate the gametes. Exflagellation is followed by free swimming, this consists of two types of flagellar beat: fast (5 beats/sec) and slow (1 beat/sec) . When free-swimming male gametes encounter a female, they adhere, this is accompanied by ‘rubbing’ of the male gamete on the female surface . The last phase is fusion of the male and female gametes, a process characterized by a period of intense flagellar beating that continues even after the male axoneme and nucleus enters the female cytoplasm .
The Plasmodium axoneme possesses a conserved 9 + 2 microtubule doublet organization, with outer and inner dynein arms and a central apparatus. However, it has been shown to assemble in a unique fashion as compared to other known eukaryotic flagella. The assembly occurs in the cytoplasm of the activated parental male gametocytes and does not rely on intraflagellar transport (IFT) [3, 4]. Flagellar activity requires significant ATP production to drive the dynein motor  and consequent sliding of the adjacent microtubule doublet . Plasmodium male gametes do not possess mitochondria [7–9] and it is unknown how they produce sufficient ATP to drive their intense flagellar beat.
This study reports the first proteomic analysis of malaria male gametes, compares it with the previously published male gametocyte proteome , and identifies novel aspect of flagellar assembly and composition and establishes glycolysis as the exclusive source of energy for microgamete motility.
Male gamete purification
A method for the purification of microgametes of Plasmodium gallinaceum was previously published , it was adapted to the rodent parasite Plasmodium berghei. Plasmodium berghei, strain ANKA clone 2.34, was maintained by cyclic passage in six to eight week-old female Tuck’s Original (TO) mice (Harlan, UK). Mice were injected intraperitoneally (ip) with 0.2 ml of 6 mg/ml phenylhydrazine (BDH Chemicals Ltd, UK) (to induce hyper-reticulocytosis) two to three days prior to infection.
At day 4 post-infection, mice were injected ip with 150 μl sulphadiazine (4 mg/ml) to remove asexual parasites . After 24 hours, parasites were harvested and gametocytes were allowed to activate in exflagellation medium (RPMI 1640 (Sigma, UK) supplemented with 25 mM Hepes (Sigma, UK) and 100 μM xanthurenic acid (Sigma, UK), pH 7.4) for 20 min. The parasites were pelleted at 500 g for 5 min and resuspended in their own supernatant; the parasites were pelleted again and the supernatant (containing extracellular male and female gametes) was harvested and spun at 10,000 g for 7 min. The pelleted samples were incubated at room temperature for 10 min, the supernatant (now containing male gametes that had swum from the pellet) was harvested and spun at 12,000 g for 10 min at 4°C and washed twice in PBS. Samples were immediately stored at -80°C. The purity and quantity of the sample was determined by microscopy following Giemsa (Sigma, UK) staining.
As described previously [13, 14], pellets were treated with a 5× solution of Invitrosol (Invitrogen, UK) and heated to 60°C for 5 min, vortexed for 2 min and sonicated for 1 hr. The solution was diluted to 1× Invitrosol with 100 mM Tris buffer (pH 8.5). Samples were reduced and carboxyamidomethylated, followed by digestion with endoproteinase Lys-C for 6 hr. The solution was diluted to 4 M urea with 100 mM Tris buffer and further digested with trypsin. Peptide mixtures were analysed by MudPIT as described previously [15, 16] with modifications. An Eksigent HPLC coupled directly to a Finnigan LTQ-Orbitrap mass spectrometer (ThermoFisher, San Jose, CA, USA) equipped with a nano-LC electrospray ionization source  was used and peptide mixtures were resolved by strong cation exchange liquid chromatography upstream of reverse-phase liquid chromatography as described .
Peptides eluted from the microcapillary column were electrosprayed directly into an LTQ-Orbitrap mass spectrometer (Thermo Fisher, USA) with the application of a distal 2.4 kV spray voltage with an inlet capillary temperature of 250°C. A cycle of one full-scan mass spectrum (300–2,000 m/z) followed by three data-dependent (window of 2 m/z) CID MS/MS spectra at a 35% normalized collision energy was repeated continuously throughout each step of the multidimensional separation.
Fully automated 11-step chromatography was carried out on each sample. From the resulting data, poor quality spectra were removed using an automated spectral quality assessment algorithm . Raw files were converted to mxzml format using MSConvert (ProteoWizard). The 339,763 MS/MS spectra from three biological replicates (GametesRep1: 102,987 MS/MS spectra, GametesRep2: 110,826 MS/MS spectra, and GametesRep3: 125,950 MS/MS spectra) were searched by PepArML  meta search engine. Mascot 2.2 , OMSSA 2.1.1 , X!Tandem 2010.01.01.4  with K-score 2010.01.01 , and S-score 2010.01.01.4 plugins, Inspect 20110313  and MyriMatch 1.5.8  search engines were used within PepArML with the following parameters: semi-specific trypsin digestion, one missed cleavage, precursor tolerance 10 ppm and fragment tolerance 0.5 Da and maximum 4 charge state, fixed carbamidomethyl modification of cysteine and variable oxidation of methionine. A custom-built FASTA database (51,833 sequences) with P. berghei (GeneDB, 2013), Human (SwissProt, 2013) and Mouse (SwissProt, 2013) sequences were used. Search results from all search engines were combined and a combination false discovery rate (FDR) was reported. Combination was performed using an unsupervised machine-learning strategy which estimates peptide identification FDR from reversed decoy searches . The search results were analysed for result interpretation in MASPECTRAS 2.0  with 1% spectra FDR and 1% peptide FDR, a minimum of two peptides for a protein, and at least five amino acids for a peptide. The identified proteins from three different biological runs were pooled for result interpretation. Protein identifications passing thresholds from human and mouse were excluded and the remaining P. berghei protein identifications were clustered according to shared peptides; clustering was performed because many proteins were isoforms, splice variants or fragments of a representative protein in each protein cluster. The data analysis system meets all standards regarding the minimum information about a proteomics experiment (MIAPE). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium  via the PRIDE partner repository  with the dataset identifier PXD001163.
Genomic and proteomic data from malaria parasites were obtained either from original papers or from PlasmoDB  or the Sanger Institute . Subcellular localization was predicted by a combination of identifying transmembrane proteins and then using a consensus of different subcellular localization predictions. Transmembrane proteins were identified using SCAMPI , tmHMM  and TOPCONS . Subcellular localization predictors used to make consensus predictors were: Wolf psort , sherloc2 , ESLPred2 , Euk mPLoc  and Cello .
Gene ontology (GO) functions were also predicted using a combination of BLAST , Pfam , Interpro  and specialized GO predictors including: ConFunc , PFP  and FFPRed . Protein structures homologous to the gamete proteins were identified by searching the fold library of the protein structure prediction server Phyre . The enzyme classification  and GO functions of the homologous structures were also used to infer the function of the gamete proteins.
For the GO enrichment analysis, the BioConductor package topGO [49, 50] was used in R version 2.10.0. This program identifies significant GO terms by taking the hierarchical structure of GOs into account. To identify significantly over-represented GO terms among the different proteomes, the ‘weight01’ algorithm within topGO was used in which genes are classed as either 0 or 1, using a minimum p-value cut-off of 0.1. All reported p-values are adjusted using a false discovery rate procedure .
Generation of PbHT-myc
One-thousand and thirty bp of the P. berghei hexose transporter gene (PBANKA_030250) were amplified in a two-step PCR to insert an EcoRV linearization site for subsequent transfection. AdvantageII Taq polymerase (Takara Bioscience) was used for all amplifications. Primers F (GGGGTACC TGGTGTATTGCATCAGTTAT, KpnI site in italics) and MR (GAAAACCTGATATCATACATCCT) as well as MF (AGGATGTATGATATC AGGTTTTC, EcoRV site in italics) and R (TTGGGCCC AACTCTTGATTTGCTTATATGTT, ApaI site in italics) were used for the first PCR. The products of these PCRs were then used as templates for the second PCR with primers F and R. The resulting fragment was inserted into vector p0007 (courtesy of J D Raine) to produce pHTmyc. This plasmid contains the hexose transporter homology region; two c-myc tags followed by the 3′UTR from P. berghei dhfr and the Toxoplasma gondii dhfr/ts resistance cassette (see Additional file 1).
Parasite transfection and pyrimethamine selection were performed as described previously using the Human T Cell Nucleofector kit (Amaxa) . Integration of the construct was monitored by Southern blot (see Additional file 1).
Samples were harvested and resuspended in 4% paraformaldehyde (PFA) (Novagen, UK) and allowed to settle on poly-L-lysine- (Sigma, UK) coated slides overnight at 4°C. The slides were washed once with Tris-buffered saline (TBS) for 5 min and then permeabilized with 0.2% Triton X-100 (Sigma, UK) in PBS. The slides were then washed three times in TBS and incubated in blocking solution (10% goat serum (Sigma, UK) and 3% BSA (Sigma, UK) in TBS) for 45 min and subsequently probed overnight at 4°C with primary antibody in 1% BSA (Sigma, UK) in TBS. Primary antibodies were rabbit anti-myc polyclonal antibody (Cell Signaling, USA) and mouse anti-alpha tubulin (Sigma, UK). The slides were washed three times in TBS and incubated for 1 hr with secondary antibody in 1% BSA (Sigma, UK) in TBS. The secondary antibodies were Alexa-488 conjugated anti-rabbit IgG and Alexa568 conjugated anti-mouse IgG (Molecular probes, UK). The slides were washed three times in TBS and mounted in Vectashield with DAPI (Vector Labs). Preparations were labelled with secondary antibodies alone to verify the absence of non-specific labelling. Parasites were visualized on a Leica SP5 confocal microscope and acquired and analysed with the LAS AF Lite software (Leica, UK).
Male gamete motility assay
Mice were infected as described above; on day 3 post-infection, tail blood was harvested and resuspended in one volume of exflagellation medium. The parasites were incubated for 10 min to allow exflagellation to take place and were then suspended for a further 10 min at room temperature in three volumes of PBS containing varying concentrations of CM3361, 2-deoxy-D-Glucose (Calbiochem, UK) and D-Glucose (Sigma, UK). The parasites were visualized by phase contrast microscopy for a maximum of 10 min on a Leica DMR microscope. Five-second videos were captured for at least 30 male gametes for each of three biological replicates in each treatment regimen using a Zeiss AxioCam HRC and Axiovision software. Videos were taken at a speed of 13 images per sec. The number of waves per second (wave frequency) was established over 5-sec periods, for gametes that displayed ‘uniform’ beat frequency for the period of observation.
Proteomic analysis identifies a male gamete proteome
This method for purifying P. berghei male gametes gave yields of 107 gametes for each sample with no microscopically detectable female contamination; the preparations did however contain mouse platelets (2.5 male gametes per platelet) and to a lesser extent erythrocyte ghosts (155.6 male gametes per erythrocyte ghost).
Three samples were prepared and subjected to MuDPIT proteomic analysis. Resulting spectra were searched against the P. berghei genome resulting in the identification of 615 unique Plasmodium proteins. In order to maximize true positive identifications and minimize false positives, the data was searched with several search engines and the results combined by an unsupervised machine learning combiner. ROC curves from each individual search engine were compared with the combined results from the machine learning combiner , using the false positive rates calculated from a random database  (see Additional file 2). The ROC curves clearly show the increases in sensitivity and specificity gained by the multiple search and combination. Protein clustering was then done on the basis of shared peptides, which removes most redundant protein identifications .
The full list of proteins identified after clustering is given in Additional file 3.
Proteins identified in the proteome for which experimental evidence suggests they play a role in male gamete biology
In-depth bioinformatics analysis of the male gamete proteome
Automated subcellular localization predictions (see Methods) were manually validated to make overall predictions. Using this approach, localizations were assigned to 581 of the 615 gamete proteins. The proteins were predicted to belong to either one or more locations in the cell, with 30% predicted to be cytoplasmic. The proteins that are currently unannotated were predominantly predicted to be either nuclear, membrane associated, flagellar, or extracellular. This approach was complemented by functional predictions (see Methods) using GO terms (see Additional file 4). The main functions predicted are for roles in transport, DNA/RNA binding and flagellar-associated functions.
Gene ontology analysis
To obtain an overview of the proteins identified and their putative function, a GO enrichment test was performed. Two enrichment tests were run: one of the male gamete proteome against all GO predictions in the genome, and one of the previously published male gametocyte proteome  against all GO predictions in the genome. Results are summarized in Additional file 4.
The male gamete and the male gametocyte exhibit significantly different GO term profiles, some of which mirror prior biological observations:
Components of DNA metabolism and DNA replication are significantly represented in the gametocyte, but only components of DNA packaging are present in the microgamete;
Constituents of protein translation are more significantly represented in the male gametocyte and less so in the male gamete;
Pathways involved in maintaining metabolic homeostasis, heat shock and stress-response are significantly represented in both cell types;
Energy metabolism in both cell types is characterized by an very significant enrichment of glycolytic and an under-representation of mitochondrial enzymes (whilst the male gametocyte contains an enlarged mitochondrion , the male gamete lacks this organelle ).
Components of the cytoskeleton and in particular microtubule and dynein-related proteins are represented in both cell types.
Energy metabolism in Plasmodium male gametes
Glycolytic enzymes identified in the proteome
P. berghei accession no
LDH L-lactate dehydrogenase
ALDO2 fructose-bisphosphate aldolase 2
FAD-dependent glycerol-3-phosphate dehydrogenase
HT hexose transporter
HAP2 generative cell specific 1
Microgametes reportedly exhibit three motility states: fast (~5 waves per sec; Additional file 5; 2.5-5 sec), slow (~1 wave per sec; Additional file 5; 0–2.5 sec) and immotile. The fast beat is essential to both forward movement and fertilization. The work required to accomplish fast beat is reportedly 100 times greater than that required for slow beat . To refine this motility analysis, the number of gametes that exhibit each motility state was scored. Interestingly, beat frequency was not changed by CM3361 (Figure 2E). Instead the proportion of male gametes displaying each motility class (fast beat, slow beat) was considerably reduced. At the lowest 2DG concentrations (0.65 and 1.25 mM), the proportion of motile gametes exhibiting slow beat, as opposed to fast, tripled when compared to controls (Figure 2C). A similar trend is observed for CM3361 (Figure 2D). At higher concentrations of both compounds, most gametes are immotile (Figure 2C and D).
The presence and reproducible detection of all enzymes of the glycolytic pathway as well as the hexose transporter (PbHT) suggest that glucose metabolism is a vital cellular activity in male gametes. The localization of PbHT to the surface of male gametes combined with the observation that glucose transport and metabolism inhibition significantly diminish male motility strongly supports this hypothesis, and are entirely consistent the detection of few mitochondrial proteins. Recognizing prior electron microscopic [1, 7], genetic  and protein tagging  studies that put beyond doubt the conclusion that the male gamete of Plasmodium lacks a mitochondrion, those proteins detected at low abundance must be present simply due to the passive inclusion of cytoplasmic mitochondrial proteins from the parental cell (which has a mitochondrion).
Glycolytic enzymes have been associated with production of ATP for the flagellar dynein motor [67–70] in organisms as diverse as the green alga Chlamydomonas reinhardtii, the kinetoplastid Trypanosma brucei procyclic form, and mammalian and sea urchin sperm. Different energy management strategies are used by these organisms. For instance, sea urchins rely on a phosphocreatine shuttle to vector an energy flux along the flagella that can rapidly reach the distal end of this long structure . In Chlamydomonas, certain glycolytic enzymes have been found in association with the axoneme or with the membrane surrounding it, indicating that at least some steps of glucose fermentation are taking place in very close proximity to the flagella . PbHT was abundant and evenly spread on the whole male gamete, that glycolysis could take place in the little cytoplasm surrounding the axoneme or the larger volume within the axoneme itself. The net balance of fermentation of one glucose molecule is two ATP, two pyruvate, two NADH and two H + molecules. The presence of lactate dehydrogenase implies that NADH is oxidized back to NAD + for continued use by GAPDH using two pyruvate and two protons. The product of this reaction is lactate, which is an acidifying factor in the cytoplasm. The resultant impact on cytoplasmic pH will have to be addressed by the cell, however surprisingly no genomic or, here, proteomic evidence for the presence of a conventional lactate exporter was found.
There was no correlation between the availability of energy (i e, concentration of inhibitor, or the presence of ‘added’ glucose) and flagellar beat frequency, but rather male gametes were seen to change the proportions of time spent in each activity (fast beat, slow beat and immotile) with changing glycolytic activity. While the energy-intensive fast beat results in efficient translocation, the biological significance of the slow beat has not been established. The observation that more slow beating male gametes are seen as inhibitor concentrations rise suggests a link between slow beat and decreased energy availability. One could speculate that this behaviour is a low-consumption holding pattern allowing the balance of metabolites (i e, import of glucose, export of glycolytic by-products) to be restored in order to allow further fast beating. Sinden and Croll  observed that the slow beat behaviour was more prevalent as the gametes aged, even in conditions where glucose concentrations would not have changed significantly (in vitro activation in high glucose medium). Male gametes may thus become less able to maintain homeostatic balance as time passes because of senescence. It is perhaps unsurprising to note that male gametes have a finite lifespan that correlates with overall beating time; they may be kept (immotile) on ice and preserve beating activity for several hours, but following >40 min of active beating, male gametes invariably become immotile.
Axoneme structure conforms to the typical 9 + 2 pattern;
The basal bodies/centrioles lack a B and C-tubule;
An outer arm dynein can be observed on most microtubule doublets;
Inner dynein arms are less frequently observed and they appear to be less electron dense than the outer arm;
No nexin links between microtubule doublets have been described;
The central apparatus is conserved at the morphological level, containing the central microtubule pair and radial spokes.Several major families of proteins identified in the eukaryotic flagellum are widely conserved (e g, tubulins, dyneins and kinesins). Within the microgamete proteome members of these protein families and the accessory proteins are presented in the context of their putative function and expression profile (Figure 3).
All major tubulins are present in the Plasmodium genome, including two subtypes of α tubulin. Α and β types form dimers that polymerize in linear arrays in microtubules, which in turn are organized/patterned by basal bodies to form axonemes. Both forms of α-tubulin and β-tubulin were found in the male gamete proteome suggesting that both α-tubulin subtypes participate in axonemal formation. The microtubule organizing centre (MTOC) tubulin types (e g, Δ,δ and ϵ) were not identified in the male gamete proteome. This is surprising since δ and ϵ type functions in other systems are intrinsically linked to centriole/basal body biology and male gametes are reportedly the only stage possessing a centriole .
Dynein arm complexes are composed of a variable number of heavy, intermediate and light chains. In this study, three outer arm heavy chains (two OADβ and one OADα) as well as two outer arm intermediate chains (IC70 and IC78) were found. This strongly suggests that, as has been hypothesized by Wickstead and Gull , the Plasmodium outer dynein arm is three-headed.
IAD-β was found in the male gamete and inner dynein arms are seen in electron micrographs of Plasmodium axonemes. Nevertheless the absence of annex components of a bona fide IAD (e g, intermediate chains 138 and 140) in the genome suggests a divergent organization of the inner arm complex.
Surprisingly only three dynein light chains were found in the male gamete proteome: LC1, LC8 and LC14. LC8 has been associated with the OAD complex  and found to interact with radial spokes ; LC1 was shown to be important for outer dynein arm function in eukaryotic flagella  but was also show to have divergent function in Plasmodium erythrocytic stages ; the function of LC14 is not known. Light chains are important in the recruitment and assembly of motor components and motor function itself [80, 81]. The possible under-representation of light chains in the male gamete proteome raises the appealing hypothesis that the light chains play a role in axoneme assembly in the gametocyte cytoplasm but are dispensable for flagellum function in the male gamete.
Three kinesins are found in the male gametocyte and the male gamete. It is difficult to speculate on the function of these proteins as kinesins also play a key role in mitosis. The microgamete kinesins identified include Kinesin-8, Kinesin-13 and an ungrouped kinesin . Kinesin-8 family members have been implicated in microtubule depolymerization [83, 84], notably in the mitotic spindle and could therefore be contained in the nucleus. Kinesin-13 has been implicated in flagellar length control in a variety of organisms . Moreover kinesin molecules have been associated with the central doublet pair and may play a role in flagellar regulation [86, 87].
The central microtubule doublet apparatus has been implicated in the regulation of flagellar beating . The accessory proteins PF16, PF20, actin and actin related-proteins, calmodulin and some conserved radial spoke proteins (Figure 3) were found in the male proteomes. PF16 was been shown to a key component for the assembly of the central apparatus of the P. berghei axoneme .
Despite having been reliably identified in the Plasmodium genome  none of the components of the cytoplasmic dynein complex (e g, cytoplasmic dynein heavy chain PBANKA_021400, cytoplasmic light chains PBANKA_041490 and PBANKA_082830), which normally engage in cargo transport along both cytoplasmic and flagellar microtubules, was found in the proteome (see Additional file 3), suggesting there is no transport of dynein-dependent cargo along the length of the male gamete axoneme.
Taken together, these observations suggest that the Plasmodium axoneme, in spite of possessing numerous highly conserved structures, is characterized by relatively few conserved core proteins. Two biological features may account for this observation: first, axoneme assembly occurs in the cytoplasm, the regulators of assembly may therefore be divergent and may not be carried over into the flagellum; second, the remarkably short life span of a male gamete might suggest any ‘maintenance apparatus’ of the flagellum is minimal or indeed absent.
This is the first analysis of the proteomic content of an apicomplexan male gamete and opens new avenues of research both into the unusual organization and biology of the Plasmodium gamete and may underpin new possibilities by which to target male gametes as a transmission blocking strategy.
We thank Christophe Morin for providing the CM3361 compound. This work was supported by research grants from the EU BioMalPar Network of Excellence, BBSRC and the Wellcome Trust for research funds, NIH grants 5R21 AI72615-2 (JRY/.), P 41 GM103533 (JRY) and Grant No. HHSN268201000032C (N01-HV-00240), NHLBI (DRG) and the Bloomberg Family Foundation/Johns Hopkins Malaria Research Institute (RRD). AMT is a recipient of support from the EU-funded Marie Curie Action MalParTraining (MEST-CT-2005–020492).
- Sinden RE, Canning EU, Bray RS, Smalley ME: Gametocyte and gamete development in Plasmodium falciparum. Proc R Soc Lond B Biol Sci. 1978, 201: 375-399.View ArticlePubMedGoogle Scholar
- Sinden RE, Croll NA: Cytology and kinetics of microgametogenesis and fertilization in Plasmodium yoelii nigeriensis. Parasitology. 1975, 70: 53-65.View ArticlePubMedGoogle Scholar
- Briggs LJ, Davidge JA, Wickstead B, Ginger ML, Gull K: More than one way to build a flagellum: comparative genomics of parasitic protozoa. Curr Biol. 2004, 14: R611-R612.View ArticlePubMedGoogle Scholar
- Wickstead B, Gull K: Dyneins across eukaryotes: a comparative genomic analysis. Traffic. 2007, 8: 1708-1721.PubMed CentralView ArticlePubMedGoogle Scholar
- Gibbons BH, Gibbons IR: Flagellar movement and adenosine triphosphatase activity in sea urchin sperm extracted with Triton X-100. J Cell Biol. 1972, 54: 75-97.PubMed CentralView ArticlePubMedGoogle Scholar
- Brokaw CJ: Bend Propagation by a sliding filament model for flagella. J Exp Biol. 1971, 55: 289-304.PubMedGoogle Scholar
- Sinden RE, Canning EU, Spain B: Gametogenesis and fertilization in Plasmodium yoelii nigeriensis - Transmission electron-microscope study. Proc R Soc Lond B Biol Sci. 1976, 193: 55-76.View ArticlePubMedGoogle Scholar
- Creasey A, Mendis K, Carlton J, Williamson D, Wilson I, Carter R: Maternal inheritance of extrachromosomal DNA in malaria parasites. Mol Biochem Parasitol. 1994, 65: 95-98.View ArticlePubMedGoogle Scholar
- Okamoto N, Spurck TP, Goodman CD, McFadden GI: Apicoplast and mitochondrion in gametocytogenesis of Plasmodium falciparum. Eukaryot Cell. 2009, 8: 128-132.PubMed CentralView ArticlePubMedGoogle Scholar
- Khan SM, Franke-Fayard B, Mair GR, Lasonder E, Janse CJ, Mann M, Waters AP: Proteome analysis of separated male and female gametocytes reveals novel sex-specific Plasmodium biology. Cell. 2005, 121: 675-687.View ArticlePubMedGoogle Scholar
- Carter R, Gwadz RW, McAuliffe FM: Plasmodium gallinaceum: Transmission-blocking immunity in chickens: I. Comparative immunogenicity of gametocyte- and gamete-containing preparations. Exp Parasitol. 1979, 47: 185-193.View ArticlePubMedGoogle Scholar
- Beetsma AL, van de Wiel TJJM, Sauerwein RW, Eling WMC: Plasmodium berghei ANKA: purification of large numbers of infectious gametocytes. Exp Parasitol. 1998, 88: 69-72.View ArticlePubMedGoogle Scholar
- Lal K, Prieto JH, Elizabeth B, Sanya J, Sanderson John R, Yates III, Jonathan M, Wastling Fiona M, Tomley Sinden RE: Characterisation of Plasmodium invasive organelles; an ookinete microneme proteome. Proteomics. 2009, 9: 1142-1151.PubMed CentralView ArticlePubMedGoogle Scholar
- Hall N, Karras M, Raine JD, Carlton JM, Kooij TWA, Berriman M, Florens L, Janssen CS, Pain A, Christophides GK, James K, Rutherford K, Harris B, Harris D, Churcher C, Quail MA, Ormond D, Doggett J, Trueman HE, Mendoza J, Bidwell SL, Rajandream MA, Carucci DJ, Yates JR, Kafatos FC, Janse CJ, Barrell B, Turner CMR, Waters AP, Sinden RE: A comprehensive survey of the Plasmodium life cycle by genomic, transcriptomic, and proteomic analyses. Science. 2005, 307: 82-86.View ArticlePubMedGoogle Scholar
- Link AJ, Eng J, Schieltz DM, Carmack E, Mize GJ, Morris DR, Garvik BM, Yates JR: Direct analysis of protein complexes using mass spectrometry. Nat Biotechnol. 1999, 17: 676-682.View ArticlePubMedGoogle Scholar
- Bradbury PC, Trager W: The fine structure of the mature gametes of Haemoproteus columbae Kruse. J Protozool. 1968, 15: 89-102.View ArticlePubMedGoogle Scholar
- Gatlin CL, Kleemann GR, Hays LG, Link AJ, Yates JR: Protein identification at the low femtomole level from silver-stained gels using a new fritless electrospray interface for liquid chromatography-microspray and nanospray mass spectrometry. Anal Biochem. 1998, 263: 93-101.View ArticlePubMedGoogle Scholar
- Washburn MP, Wolters D, Yates JR: Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat Biotechnol. 2001, 19: 242-247.View ArticlePubMedGoogle Scholar
- Bern M, Goldberg D, McDonald WH, Yates JR: Automatic quality assessment of peptide tandem mass spectra. Bioinformatics. 2004, 20: i49-i54.View ArticlePubMedGoogle Scholar
- Edwards N, Wu X, Tseng C-W: An unsupervised, model-free, machine-learning combiner for peptide identifications from tandem mass spectra. Clin Proteomics. 2009, 5: 23-36.View ArticleGoogle Scholar
- Perkins DN: Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis. 1999, 20: 3551-3567.View ArticlePubMedGoogle Scholar
- Geer LY, Markey SP, Kowalak JA, Wagner L, Xu M, Maynard DM, Yang X, Shi W, Bryant SH: Open mass spectrometry search algorithm. J Proteome Res. 2004, 3: 958-964.View ArticlePubMedGoogle Scholar
- Craig R, Beavis RC: TANDEM: matching proteins with tandem mass spectra. Bioinformatics. 2004, 20: 1466-1467.View ArticlePubMedGoogle Scholar
- Maclean B, Jimmy KE, Ronald CB, Martin M: General framework for developing and evaluating database scoring algorithms using the TANDEM search engine. Bioinformatics. 2006, 22: 2830-2832.View ArticlePubMedGoogle Scholar
- Tanner S, Shu H, Frank A, Wang L-C, Zandi E, Mumby M, Pevzner PA, Bafna V: InsPecT: identification of posttranslationally modified peptides from tandem mass spectra. Anal Chem. 2005, 77: 4626-4639.View ArticlePubMedGoogle Scholar
- Tabb DL, Fernando CG, Chambers MC: MyriMatch: Highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis. J Proteome Res. 2007, 6: 654-661.PubMed CentralView ArticlePubMedGoogle Scholar
- Elias JE, Gygi SP: Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat Methods. 2007, 4: 207-214.View ArticlePubMedGoogle Scholar
- Mohien CU, Hartler J, Breitwieser F, Rix U, Rix LR, Winter GE, Thallinger GG, Bennett KL, Superti-Furga G, Trajanoski Z, Colinge J: MASPECTRAS 2: An integration and analysis platform for proteomic data. Proteomics. 2010, 10: 2719-2722.View ArticleGoogle Scholar
- ProteomeXchange consortium. [http://proteomecentral.proteomexchange.org]
- Vizcaino JA, Deutsch EW, Wang R, Csordas A, Reisinger F, Rios D, Dianes JA, Sun Z, Farrah T, Bandeira N, Binz P-A, Xenarios I, Eisenacher M, Mayer G, Gatto L, Campos A, Chalkley RJ, Kraus H-J, Albar JP, Martinez-Bartolome S, Apweiler R, Omenn GS, Martens L, Jones AR, Hermjakob H: ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol. 2014, 32: 223-226.PubMed CentralView ArticlePubMedGoogle Scholar
- PlasmoDB. [http://www.plasmodb.org]
- Sanger Institute. [http://www.sanger.ac.uk/Projects/Protozoa/]
- Bernsel A, Viklund H, Falk J, Lindahl E, von Heijne G, Elofsson A: Prediction of membrane-protein topology from first principles. Proc Natl Acad Sci U S A. 2008, 105: 7177-7181.PubMed CentralView ArticlePubMedGoogle Scholar
- Krogh A, Larsson B, von Heijne G, Sonnhammer EL: Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J Mol Biol. 2001, 305: 567-580.View ArticlePubMedGoogle Scholar
- Bernsel A, Viklund H, Hennerdal A, Elofsson A: TOPCONS: consensus prediction of membrane protein topology. Nucleic Acids Res. 2009, 37: W465-W468.PubMed CentralView ArticlePubMedGoogle Scholar
- Horton P, Park KJ, Obayashi T, Fujita N, Harada H, Adams-Collier CJ, Nakai K: WoLF PSORT: protein localization predictor. Nucleic Acids Res. 2007, 35: W585-W587.PubMed CentralView ArticlePubMedGoogle Scholar
- Briesemeister S, Blum T, Brady S, Lam Y, Kohlbacher O, Shatkay H: SherLoc2: a high-accuracy hybrid method for predicting subcellular localization of proteins. J Proteome Res. 2009, 8: 5363-5366.View ArticlePubMedGoogle Scholar
- Garg A, Raghava G: ESLpred2: improved method for predicting subcellular localization of eukaryotic proteins. BMC Bioinformatics. 2008, 9: 503-PubMed CentralView ArticlePubMedGoogle Scholar
- Chou KC, Shen HB: A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0. PLoS One. 2010, 5: e9931-PubMed CentralView ArticlePubMedGoogle Scholar
- Yu CS, Chen YC, Lu CH, Hwang JK: Prediction of protein subcellular localization. Proteins. 2006, 64: 643-651.View ArticlePubMedGoogle Scholar
- Altschul SF, Madden TL, Schüffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25: 3389-3402.PubMed CentralView ArticlePubMedGoogle Scholar
- Punta M, Coggill PC, Eberhardt RY, Mistry J, Tate J, Boursnell C, Pang N, Forslund K, Ceric G, Clements J, Heger A, Holm L, Sonnhammer ELL, Eddy SR, Bateman A, Finn RD: The Pfam protein families database. Nucleic Acids Res. 2012, 40: D290-D301.PubMed CentralView ArticlePubMedGoogle Scholar
- Hunter S, Jones P, Mitchell A, Apweiler R, Attwood TK, Bateman A, Bernard T, Binns D, Bork P, Burge S, de Castro E, Coggill P, Corbett M, Das U, Daugherty L, Duquenne L, Finn RD, Fraser M, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J: InterPro in 2011: new developments in the family and domain prediction database. Nucleic Acids Res. 2012, 40: D306-D312.PubMed CentralView ArticlePubMedGoogle Scholar
- Wass MN, Sternberg MJ: ConFunc–functional annotation in the twilight zone. Bioinformatics. 2008, 24: 798-806.View ArticlePubMedGoogle Scholar
- Hawkins T, Luban S, Kihara D: Enhanced automated function prediction using distantly related sequences and contextual association by PFP. Protein Sci. 2006, 15: 1550-1556.PubMed CentralView ArticlePubMedGoogle Scholar
- Lobley AE, Nugent T, Orengo CA, Jones DT: FFPred: an integrated feature-based function prediction server for vertebrate proteomes. Nucleic Acids Res. 2008, 36: W297-W302.PubMed CentralView ArticlePubMedGoogle Scholar
- Kelley LA, Sternberg MJ: Protein structure prediction on the Web: a case study using the Phyre server. Nat Protoc. 2009, 4: 363-371.View ArticlePubMedGoogle Scholar
- Bairoch A: The ENZYME database in 2000. Nucleic Acids Res. 2000, 28: 304-305.PubMed CentralView ArticlePubMedGoogle Scholar
- Alexa A, Rahnenfuhrer J, Lengauer T: Improved scoring of functional groups from gene expression data by decorrelating GO graph structure. Bioinformatics. 2006, 22: 1600-1607.View ArticlePubMedGoogle Scholar
- Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge YC, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang JH: Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004, 5: R80-PubMed CentralView ArticlePubMedGoogle Scholar
- Benjamini Y, Yekutieli D: The control of the false discovery rate in multiple testing under dependency. Annu Stat. 2001, 29: 1165-1188.View ArticleGoogle Scholar
- Janse CJ, Franke-Fayard B, Mair GR, Ramesar J, Thiel C, Engelmann S, Matuschewski K, van Gemert GJ, Sauerwein RW, Waters AP: High efficiency transfection of Plasmodium berghe i facilitates novel selection procedures. Mol Biochem Parasitol. 2006, 145: 60-70.View ArticlePubMedGoogle Scholar
- Billker O, Dechamps S, Tewari R, Wenig G, Franke-Fayard B, Brinkmann V: Calcium and a calcium-dependent protein kinase regulate gamete formation and mosquito transmission in a malaria parasite. Cell. 2004, 117: 503-514.View ArticlePubMedGoogle Scholar
- Liu YJ, Tewari R, Ning J, Blagborough AM, Garbom S, Pei JM, Grishin NV, Steele RE, Sinden RE, Snell WJ, Billker O: The conserved plant sterility gene HAP2 functions after attachment of fusogenic membranes in Chlamydomonas and Plasmodium gametes. Genes Dev. 2008, 22: 1051-1068.PubMed CentralView ArticlePubMedGoogle Scholar
- Tewari R, Dorin D, Moon R, Doerig C, Billker O: An atypical mitogen-activated protein kinase controls cytokinesis and flagellar motility during male gamete formation in a malaria parasite. Mol Microbiol. 2005, 58: 1253-1263.View ArticlePubMedGoogle Scholar
- Eksi S, Williamson KC: Male-specific expression of the paralog of malaria transmission-blocking target antigen Pfs230, PfB0400w. Mol Biochem Parasitol. 2002, 122: 127-130.View ArticlePubMedGoogle Scholar
- van Dijk MR, Janse CJ, Thompson J, Waters AP, Braks JAM, Dodemont HJ, Stunnenberg HG, van Gemert G-J, Sauerwein RW, Eling W: A central role for P48/45 in malaria parasite male gamete fertility. Cell. 2001, 104: 153-164.View ArticlePubMedGoogle Scholar
- Eksi S, Czesny B, van Gemert GJ, Sauerwein RW, Eling W, Williamson KC: Malaria transmission-blocking antigen, Pfs230, mediates human red blood cell binding to exflagellating male parasites and oocyst production. Mol Microbiol. 2006, 61: 991-998.View ArticlePubMedGoogle Scholar
- Lal K, Delves MJ, Bromley E, Wastling JM, Tomley FM, Sinden RE: Plasmodium male development gene-1 (mdv-1) is important for female sexual development and identifies a polarised plasma membrane during zygote development. Int J Parasitol. 2009, 39: 755-761.View ArticlePubMedGoogle Scholar
- Talman AM, Lacroix C, Marques SR, Blagborough AM, Carzaniga R, Ménard R, Sinden RE: PbGEST mediates malaria transmission to both mosquito and vertebrate host. Mol Microbiol. 2011, 82: 462-474.View ArticlePubMedGoogle Scholar
- Straschil U, Talman AM, Ferguson DJ, Bunting KA, Xu Z, Bailes E, Sinden RE, Holder AA, Smith EF, Coates JC, Tewari R: The Armadillo repeat protein PF16 is essential for flagellar structure and function in Plasmodium male gametes. PLoS One. 2010, 5: e12901-PubMed CentralView ArticlePubMedGoogle Scholar
- Deligianni E, Morgan RN, Bertuccini L, Kooij TW, Laforge A, Nahar C, Poulakakis N, Schüler H, Louis C, Matuschewski K, Siden-Kiamos I: Critical role for a stage-specific actin in male exflagellation of the malaria parasite. Cell Microbiol. 2011, 13: 1714-1730.View ArticlePubMedGoogle Scholar
- Slavic K, Straschil U, Reininger L, Doerig C, Morin C, Tewari R, Krishna S: Life cycle studies of the hexose transporter of Plasmodium species and genetic validation of their essentiality. Mol Microbiol. 2010, 75: 1402-1413.PubMed CentralView ArticlePubMedGoogle Scholar
- Joet T, Eckstein-Ludwig U, Morin C, Krishna S: Validation of the hexose transporter of Plasmodium falciparum as a novel drug target. Proc Natl Acad Sci U S A. 2003, 100: 7476-7479.PubMed CentralView ArticlePubMedGoogle Scholar
- van Schalkwyk DA, Priebe W, Saliba KJ: The inhibitory effect of 2-halo derivatives of D-glucose on glycolysis and on the proliferation of the human malaria parasite Plasmodium falciparum. J Pharmacol Exp Ther. 2008, 327: 511-517.View ArticlePubMedGoogle Scholar
- Vaidya AB, Morrisey J, Plowe CV, Kaslow DC, Wellems TE: Unidirectional dominance of cytoplasmic inheritance in 2 genetic crosses of Plasmodium falciparum. Mol Cell Biol. 1993, 13: 7349-7357.PubMed CentralView ArticlePubMedGoogle Scholar
- Krisfalusi M, Miki K, Magyar PL, O’Brien DA: Multiple glycolytic enzymes are tightly bound to the fibrous sheath of mouse spermatozoa. Biol Reprod. 2006, 75: 270-278.View ArticlePubMedGoogle Scholar
- Mitchell BF, Pedersen LB, Feely M, Rosenbaum JL, Mitchell DR: ATP Production in Chlamydomonas reinhardtii flagella by glycolytic enzymes. Mol Biol Cell. 2005, 16: 4509-4518.PubMed CentralView ArticlePubMedGoogle Scholar
- Ford WCL: Glycolysis and sperm motility: does a spoonful of sugar help the flagellum go round?. Hum Reprod Update. 2006, 12: 269-274.View ArticlePubMedGoogle Scholar
- Oberholzer M, Bregy P, Marti G, Minca M, Peier M, Seebeck T: Trypanosomes and mammalian sperm: one of a kind?. Trends Parasitol. 2007, 23: 71-77.View ArticlePubMedGoogle Scholar
- Tombes RM, Shapiro BM: Metabolite channeling: A phosphorylcreatine shuttle to mediate high energy phosphate transport between sperm mitochondrion and tail. Cell. 1985, 41: 325-334.View ArticlePubMedGoogle Scholar
- Aikawa M, Carter R, Ito Y, Nijhout MM: New observations on gametogenesis, fertilization, and zygote transformation in Plasmodium gallinaceum. J Protozool. 1984, 31: 403-413.View ArticlePubMedGoogle Scholar
- Aikawa M, Huff CG, Strome CPA: Morphological study of microgametogenesis of Leucocytozoon simondi. J Ultrastruct Res. 1970, 32: 43-68.View ArticlePubMedGoogle Scholar
- Aikawa M, Sterling C: High-voltage electron-microscopy on microgametogenesis of Haemoproteus columbae. Z Zellforsch Mikrosk Anat. 1974, 147: 353-360.View ArticlePubMedGoogle Scholar
- Sinden RE: Cell Biology. Rodent Malaria. Edited by: Killick-Kendrick R. 1980, London: Academic Press, 85-169.Google Scholar
- Pfister K, Fay R, Witman G: Purification and polypeptide composition of dynein ATPases from Chlamydomonas flagella. Cell Motil. 1982, 2: 525-547.View ArticlePubMedGoogle Scholar
- Yang P, Diener DR, Yang C, Kohno T, Pazour GJ, Dienes JM, Agrin NS, King SM, Sale WS, Kamiya R, Rosenbaum JL, Witman GB: Radial spoke proteins of Chlamydomonas flagella. J Cell Sci. 2006, 119: 1165-1174.PubMed CentralView ArticlePubMedGoogle Scholar
- Baron DM, Kabututu ZP, Hill KL: Stuck in reverse: loss of LC1 in Trypanosoma brucei disrupts outer dynein arms and leads to reverse flagellar beat and backward movement. J Cell Sci. 2007, 120: 1513-1520.View ArticlePubMedGoogle Scholar
- Daher W, Pierrot C, Kalamou H, Pinder JC, Margos G, Dive D, Franke-Fayard B, Janse CJ, Khalife J: Plasmodium falciparum dynein light chain 1 interacts with actin/myosin during blood stage development. J Biol Chem. 2010, 285: 20180-20191.PubMed CentralView ArticlePubMedGoogle Scholar
- King SM: The dynein microtubule motor. Biochim Biophys Acta. 2000, 1496: 60-75.View ArticlePubMedGoogle Scholar
- Sakato M, King SM: Design and regulation of the AAA + microtubule motor dynein. J Struct Biol. 2004, 146: 58-71.View ArticlePubMedGoogle Scholar
- Wickstead B, Gull K: A “Holistic” kinesin phylogeny reveals new kinesin families and predicts protein functions. Mol Biol Cell. 2006, 17: 1734-1743.PubMed CentralView ArticlePubMedGoogle Scholar
- Gupta ML, Carvalho P, Roof DM, Pellman D: Plus end-specific depolymerase activity of Kip3, a kinesin-8 protein, explains its role in positioning the yeast mitotic spindle. Nat Cell Biol. 2006, 8: 913-923.View ArticlePubMedGoogle Scholar
- Stumpff J, von Dassow G, Wagenbach M, Asbury C, Wordeman L: The kinesin-8 motor Kif18A suppresses kinetochore movements to control mitotic chromosome alignment. Dev Cell. 2008, 14: 252-262.PubMed CentralView ArticlePubMedGoogle Scholar
- Dawson SC, Sagolla MS, Mancuso JJ, Woessner DJ, House SA, Fritz-Laylin L, Cande WZ: Kinesin-13 regulates flagellar, interphase, and mitotic microtubule dynamics in Giardia intestinalis. Eukaryot Cell. 2007, 6: 2354-2364.PubMed CentralView ArticlePubMedGoogle Scholar
- Fox L, Sawin K, Sale W: Kinesin-related proteins in eukaryiotic flagella. J Cell Sci. 1994, 107: 1545-1550.PubMedGoogle Scholar
- Yokoyama R, O’Toole E, Ghosh S, Mitchell D: Regulation of flagellar dynein activity by a central pair kinesin. Proc Natl Acad Sci U S A. 2004, 101: 17398-17403.PubMed CentralView ArticlePubMedGoogle Scholar
- Smith EF, Lefebvre PA: The role of central apparatus components in flagellar motility and microtubule assembly. Cell Motil. 1997, 38: 1-8.View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.