Bacterium excluded from the Eukaryote Club

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It’s something you learn in high school – there are two basic approaches to cellular life – prokaryotes (bacteria and archaea) and eukaryotes (the rest of us – aardvarks, amoebae, apricots, etc.). Prokaryotes have an open-plan office, with all biological functions carried out in the one cellular space. Eukaryotes, however, have dedicated compartments for the chief executive (nucleus), finance (mitochondria), sales and marketing (golgi, endoplasmic reticulum), and so on.

One of the electron microscope images used for this study. Green - outer membrane. Cyan - inner membrane. Yellow - DNA.

One of the electron microscope images used for this study. Green – outer membrane. Cyan – inner membrane. Yellow – DNA.

But every now and then you get an upstart prokaryote that seems to have ideas above its station. One such is Gemmata obscuriglobus, an exemplar of a bunch of unusual bugs known as the PVC superphylum (for Planctomycetes, Verrucomicrobiae, Chlamydiae). Gemmata has a complex membrane structure, and previous studies of its 3D configuration have suggested that this bacterium has a compartmentalised cell, eukaryote-style, its genetic material encapsulated in a nucleus-like body.

With a nice combination of technical wizardry and sheer hard work, Rachel Santarella-Mellwig, Damien Devos and colleagues, authors of a paper just published in PLOS Biology, have managed to reconstruct the structure of the internal membranes of a typical Gemmata cell in spectacular detail. They embedded ten bugs in plastic, chopped them each into ten or so slices, and then took electron microscope snapshots of the Gemmata salami. In the absence of software that could do the job, they then manually tracked and assigned the membranes in each slice, building up a detailed 3D model of the membranes and other features.

Two slices through a 3D model of the same Gemmata cell, showing the continuous space enclosed by the inner membrane (cyan).

Two slices through a 3D model of the same Gemmata cell, showing the continuous space enclosed by the inner membrane (cyan).

The answer, perhaps sadly, is that Gemmata is actually rather a traditional bug, topologically speaking. The beautiful pictures and movies produced by the authors reveal a membrane system that, while extremely convoluted, doesn’t enclose any separate compartments. Gemmata is as prokaryotic as they come.

The authors propose that a common ancestor of the PVC superphylum evolved a way to fold its membrane up. But what’s the point of this? They draw the comparison with lab workhorse and tabloid horror story, Escherichia coli – the archetypal bug body-plan. Both Gemmata and E. coli are what’s called “gram-negative” bugs, in that they have two membranes – one outside the cell wall, and one inside it – separated by the periplasmic space. As an aside, it had been thought that Gemmata might lack an outer membrane – this study clearly shows that it does have one after all, and that the cytoplasm and the periplasm are the only two topologically closed compartments.

Gemmata is a 2-micron sphere. E. coli is a rod-shaped thing about 1.5 microns long. In each case the periplasmic space – the gap between the membranes – accounts for about a third of the cell’s total volume. However, the difference really shows up when you look at membrane surface area – in the classic bug E. coli the inner and outer membranes have almost identical surface areas, but the convolutions of the Gemmata inner membrane give it three times the area of the outer membrane.

The purpose of this extra membrane surface area is obscure, but the authors draw parallels with the eukaryotic endoplasmic reticulum and speculate that Gemmata and other PVC members might use it for the synthesis of sterols. Sterols are complex chemicals used by eukaryotes for signalling purposes and to modify the physical properties of membranes. However, Gemmata and its relatives are thought to be among the few bacteria capable of making sterols, and the authors imply that the association with a fancy membrane structure may not be a coincidence.

Despite the disappointing lack of full-blown compartmentalisation, there are striking similarities between the fancy internal membrane of the PVC bacteria and the endoplasmic reticulum of eukaryotes. Are the PVCs an evolutionary link between classic gram negative bugs and us, or have these common membrane features (high surface area, sterol synthesis, decoration with ribosomes)  arisen twice in evolution?

ResearchBlogging.org

Santarella-Mellwig, R., Pruggnaller, S., Roos, N., Mattaj, I., & Devos, D. (2013). Three-Dimensional Reconstruction of Bacteria with a Complex Endomembrane System PLoS Biology, 11 (5) DOI: 10.1371/journal.pbio.1001565

 

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Open for microbiology: PLOS Biology at ASM 2013

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As we have discussed in previous posts, PLOS Biology believes strongly that we are Open for a Reason; one of our key aims is to publish high quality research in areas of importance to ensure that it reaches the widest possible audience without any barriers to access.  Microbiological research is an area of research that we believe should be as openly available as is possible  by being published in an open access, CC-BY journal with associated data mineable and reusable.

PLOS Biology publishes many interesting and high profile studies from the field of microbiology – to give you a taste of what we’ve recently published, check out the links  we’ve provided below to access latest research in this field.

From tomorrow, I will be attending the 113th General Meeting of the American Society for Microbiology in Denver, Colorado, together with my colleagues from PLOS ONE, where I look forward to meeting with our Academic Editors, authors and reviewers in the microbiology research community.

If you’re also attending and would like to find out more about how to publish in an Open Access journal, please visit us at the PLOS booth, number 350, where you can meet with myself and my fellow PLOS colleagues. PLOS Biology is also planning a Meet the editor session from 1:30-3.30pm on Sunday 19th May, so come by then, or stop by another time to leave me a message (or alternatively email me at biologue[at]plos.org). Looking forward to meeting you in Denver.

 

If you’re interested in microbiology, you might want to read ….

(and of course you can because they are published in PLOS Biology and all Open Access….)

Cooperation and the Fate of Microbial Societies

The Evolution of Mutualism in Gut Microbiota Via Host Epithelial Selection

Selecting One of Several Mating Types through Gene Segment Joining and Deletion in Tetrahymena thermophila

Conformational Change-Induced Repeat Domain Expansion Regulates Rap Phosphatase Quorum-Sensing Signal Receptors

Structural Basis of Rap Phosphatase Inhibition by Phr Peptides

Candida albicans Commensalism and Pathogenicity Are Intertwined Traits Directed by a Tightly Knit Transcriptional Regulatory Circuit

When the Most Potent Combination of Antibiotics Selects for the Greatest Bacterial Load: The Smile-Frown Transition

The Human Microbiome Project: A Community Resource for the Healthy Human Microbiome

Microtubules in Bacteria: Ancient Tubulins Build a Five-Protofilament Homolog of the Eukaryotic Cytoskeleton

 

 

 

 

 

 

 

 

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How do you like your fish? Phylogenised!

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The bony fishes are one of the success stories of life on planet earth, diverse in shape and habit, and thriving in almost every body of water on the globe. Estimates of the number of distinct species tend to be around the 30,000 mark, but the real number is likely to be much higher. We eat them, admire them in aquaria and on David Attenborough films, and threaten their existence with our way of life. But how did this flowering of supremely adapted aquatic and marine animals come about? Two papers just published in PLOS Currents Tree of Life give us the most comprehensive fish family tree yet.

Taxonomy, or the hierarchical categorisation of species according to their perceived similarity, has been with us for centuries, sometimes pursued by the gentle clergyman trying to document God’s creation. Taxonomy’s hard-nosed descendent, phylogenetics, aims to re-jig this endeavour in the light of the recognition that these hierarchical similarities didn’t arise by chance, but instead reflect the real underlying hierarchical divergence of things that are related, by descent, via common ancestors. Dogs look more like cats than either looks like a frog – not because an omnipotent being liked to make his creations in boxed sets, but because the dog ancestor split from the cat ancestor after the dog/cat ancestor split from the frog ancestor.

Since that recognition, phylogenetics has revisited the question of establishing the true “Tree of Life” – a pattern of relatedness that reflects the actual order of divergence of ancestors from each other, giving rise to the richness of extant species that we see around us today and those extinct ones whose traces we find in the rocks below our feet. While you can use data about almost any aspect of an organism to make a phylogenetic tree, most studies tend to use genetic sequence data because of its sheer abundance, relative objectivity and statistical tractability.

Collapsed higher-level phylogenetic tree of all bony fishes. From Betancur-R et al., PLOS Currents Tree of Life.

Collapsed higher-level phylogenetic tree of all bony fishes. From Betancur-R et al., PLOS Currents Tree of Life.

Two papers from Ricardo Betancur-R., Richard Broughton, Guillermo Orti and colleagues, published last month in PLOS Currents Tree of Life (Betancur-R et al., Broughton et al.), aim to provide a definitive answer. This massively comprehensive survey takes in 1410 separate species of bony fish, adding in four tetrapods (human, mouse, opossum, frog) and two non-bony cartilaginous fish (shark, ray) for good measure. They use sequences from twenty-one different genes to give a high-resolution and strongly supported family tree of the extant bony fishes that live on our planet. They also use data from the fossil record to pin down the likely timescale of key divergence events in the tree.

The papers contain a vast amount of information, and the sheer scale and resolution of the study means that the tree has to be broken down into many sub-trees to be presented on paper – a clear case for the infinitely zoomable tree viewer, OneZoom. The one aspect that I’d like to pick out for this blog post is the deepest split in the bony fish family tree – the one that gives rise to Actinopteryigians and Sarcopterygians. The Actinopterygians are the things that you see in the fishmongers – fish with a capital “F” – ray-finned fish. The Sarcopterygians, however, are a really interesting bunch. They comprise coelacanths, lungfishes and tetrapods like you and me. Fish that have gone places.

The papers show conclusively that the Actinopteryigians and Sarcopterygians are indeed distinct groups (“mutually monophyletic”), that lungfishes, rather than coelacanths, are our closest cousins, and that the split between these major groups can be dated to 427 million years ago in the Middle Silurian. We left the coelacanths behind 18 million years later in the Early Devonian. Meanwhile, our more distant ray-finned cousins, the Actinopterygians, started to break out into their oldest extant groups, with birchirs and reedfish peeling off in the Late Devonian, sturgeons and paddlefish in the Early Carboniferous and gars and bowfin in the Middle Carboniferous.

There have been many phylogenies of fish to date, and there are sure to be many more in the future (the addition of more species and the use of more genes per species would trump these studies). However, with 1093 genera from 369 families, representing all known orders, the PLOS Currents papers are close to providing a definitive picture, and have the potential to provide a solid platform for future comparative studies of these amazing animals.

The six strands of PLOS Currents.

The six strands of PLOS Currents.

The other thing perhaps worth mentioning is the way in which these papers were published – PLOS Currents is a strand of PLOS that shares some attributes with conventional publishing – it’s fully peer-reviewed, and indexed by PubMed and Scopus, for example. However, it has some radical features that set it apart. It allows authors to have complete control over the publication process, writing the paper and determining the final format, all within the PLOS Currents platform. Like PLOS ONE, it doesn’t try to make the call on perceived impact, but unlike PLOS ONE, it will consider simpler, less narrative items for publication – “single figures or experiments, research in progress, protocols, datasets”. In addition, a structured versioning system means that you can go on updating papers after their initial publication. I’ve half a mind to dust off some of my old autorads…

 

ResearchBlogging.org

Betancur-R., R., Broughton, R., Wiley, E., Carpenter, K., López, J., Li, C., Holcroft, N., Arcila, D., Sanciangco, M., Cureton II, J., Zhang, F., Buser, T., Campbell, M., Ballesteros, J., Roa-Varon, A., Willis, S., Borden, W., Rowley, T., Reneau, P., Hough, D., Lu, G., Grande, T., Arratia, G., & Ortí, G. (2013). The Tree of Life and a New Classification of Bony Fishes PLoS Currents DOI: 10.1371/currents.tol.53ba26640df0ccaee75bb165c8c26288

ResearchBlogging.org

Broughton, R., Betancur-R., R., Li, C., Arratia, G., & Ortí, G. (2013). Multi-locus phylogenetic analysis reveals the pattern and tempo of bony fish evolution PLoS Currents DOI: 10.1371/currents.tol.2ca8041495ffafd0c92756e75247483e

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How petals shape up

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Have you ever marveled at a summer meadow in full bloom? And maybe even wondered how it is that flowers and their petals come in so many beautiful and different shapes?

Image credit: Jonathan Billinger via Wikimedia Commons

Image credit: Jonathan Billinger via Wikimedia Commons

Well, new findings published in PLOS Biology reveal a hidden map within growing petals that directs how they are shaped as they develop. And what’s really intriguing about this work is that a similar hidden map is known to also direct how leaves take shape, revealing that plants use a similar strategy to shape two  plant organs with very different functions  – one attracts pollinators, while the other is the main site for photosynthesis and respiration.

Enrico Coen and colleagues have been investigating for several years now how it is that plant buds form the diverse flower and leaf shapes that we see around us.  In an earlier study, this team uncovered the existence of a so-called polarity field in the developing leaves of the plant Arabidopsis. This field, they discovered,  converges towards the tip of the leaf and determines rates of cell growth both parallel and perpendicular to this field. In essence, it orients patterns of growth so that they give rise to the characteristic shape of Arabidopsis leaves: elliptical and narrow towards the tip.

Arabidopsis petals by contrast aren’t pointed at their tips but are rounded in shape rather like a paddle. To find out how petals acquire this shape, Coen and his team turned to both experimental approaches and computer modelling. First, they measured and analyzed petal shape and the patterns of growth in developing petals. They then compared different computer models to see which would most accurately predict the patterns of growth and shapes they’d seen in real petals. The first simulation they tried used a polarity pattern similar to that found Arabidopsis flowersin the leaf; however this model (the “convergent model”) didn’t produce virtual petal shapes that matched real ones.  So instead, the researchers tested a different polarity pattern – the “divergent model” - in which the polarity field fans outward. This model produced virtual petals that looked much more like the petals of Arabidopsis flowers.

In both organs, what helps to form this hidden polarity map is the plant hormone auxin, which regulates plant growth and is transported around plant cells in specific directions. This directional movement of auxin, called polar auxin transport, is determined by where PIN proteins  - which move auxin out of plant cells – are located in cell membranes. In their PLOS Biology study, Coen and colleagues found that the location of PIN1 in petal epidermal cells indicates that auxin is transported in many directions in a petal and not only towards the tip, as occurs in leavesthis contributes to a different pattern of growth and ultimately to a different shape. They also show how a protein called Jagged has a key role in promoting increased rates of growth at the tips of petals and how it also influences the extent of this divergent polarity field.

So together these findings show that plants can create differently shaped organs by altering a common, auxin-based map that determines where and in what direction different rates of growth occur. And that in turn helps to answer the larger question of how it is that plants shape their different tissues despite their cells being unable to escape the constraints of the plant cell wall and move around to create new shapes (as happens in animal cells). It partly comes down to growth – where it occurs and how quickly – and how that growth can be influenced by an underlying polarity field to sculpt the complex shapes that attract the bee and please the human eye.

 

ResearchBlogging.org

Susanna Sauret-Güeto, Katharina Schiessl, Andrew Bangham, Robert Sablowski, Enrico Coen (2013). JAGGED Controls Arabidopsis Petal Growth and Shape by Interacting with a Divergent Polarity Field PLOS Biology, 11 (4) : 10.1371/journal.pbio.1001550

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We want you to design the 2013 PLOS Computational Biology T-shirt!

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This year’s PLOS Computational Biology t-shirt will debut at July’s ISMB/ECCB 2013 meeting in Berlin. To enter the competition, send your design to ploscompbiol[at]plos.org by Tuesday May 14th 2013.

The winning design from our 2010 competition, courtesy of Kifayathullah Liakath Ali

The winning design from our 2010 competition, by Kifayathullah Liakath Ali

For the fourth year in a row, we’re calling on scientists and designers to send us eye-catching designs that appeal to the computational biology community and encapsulate a recent advance or innovation in the field. The creator(s) of the winning design will receive a free t-shirt and a write-up of their design and research on PLOS Biologue (see this one about the 2010 competition winner), not to mention full bragging rights!

Design Requirements–please review these carefully as they have changed significantly from past years’ requirements.

  • Style: Keep your design simple, readable and visible–type at 12pt or larger; lines at 4pt or larger
  • Logo: Do not include the PLOS Computational Biology logo or name in your design; this would be added later
  • Colors: Solid colors only (max. of 4 colors), with no shading
  • No Photographs or complex dimensional images
  • Maximum size: 12” x 12” (30cm x 30cm)
  • Resolution: 150 ppi minimum (pixels per inch); must be sharp (fuzzy images will not be accepted)
  • No Background: Do not include any background (white or color) behind your image
  • Acceptable File Types: Original layered files .psd, .eps, .ai, or .pdf (hi-resolution)
  • Your design does not have to originate from a PLOS article. But if it does, then please include a URL to the PLOS article and a brief explanation of your design.
  • Please do not submit images that have been published by another publisher.
  • PLOS will place your design on a t-shirt made specifically for PLOS Computational Biology.  PLOS will determine the overall design of the t-shirt with the winning image placed to fit while following the organization’s style guide requirements.

What do you want to see on the front of the 2013 PLOS Computational Biology t-shirt? Please contact us at ploscompbiol[at]plos.org with your designs and any queries. We look forward to hearing from you!

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PLOS Biology – open for cancer research

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Cancer, the big C, is not just a single disease; it is a complex beast that, according to data from the National Cancer Institute, will be diagnosed in 1 in 2 people during their lifetime. The Editorial team at PLOS Biology believes strongly that we are Open for a Reason, precisely so that research in areas of high importance reaches the widest audience.  Cancer research is one such area that should be as openly available as possible, with associated data mineable and reusable, ideally in an open access, CC-BY journal as quickly as possible.

Cancer can take hold in numerous locations in the body, can metastasize and travel to other sites, and generally results from cumulative mutations in many genes and pathways. Although the (open access) Annual Report to the Nation on the Status of Cancer [1] reports an encouraging overall decline in cancer death rates, many of us will have lost someone, or know someone currently battling with cancer, and it continues to devastate lives.

Despite research and advanced treatment options leading to an increased survival rate for many kinds of cancer, there is still a lot that we don’t understand. Cancer research does not encapsulate just one small area of research, instead it encompasses investigations across a broad range of mechanisms in many genes and pathways using a range of model organisms, not least, humans. Many questions remain as to what triggers the onset of cancer, tumour progression and metastasis; how we can best identify new targets for drug development; and of course how best to treat the disease in its many forms.

Given the worldwide impact of cancer from a financial and economic perspective, as well as from a more emotive one, publishing cancer research in an open access forum is one way to ensure that those who need access to  AACR2_300x250research discoveries from across this broad field have that access as quickly and as easily as possible. PLOS Biology is open for just this reason, and we publish many high impact publications that relate to cancer one way or another. For this reason, we encourage cancer researchers to consider PLOS Biology as a high visibility venue for your future research. We are interested in all areas of cancer research traversing the bedside-to-bench spectrum, and we welcome translational studies.

Later this week, I will be representing PLOS Biology at the American Association of Cancer Research (AACR) Annual Meeting 2013, along with colleagues from PLOS Medicine and PLOS ONE.  Last year at the AACR meeting, there were nearly 17,000 attendees from 70 countries; based in Washington DC this year, no doubt thousands will again gather to discuss the latest, most interesting findings in all areas of cancer research.

If you’re attending and want to find out more about how to publish in an Open Access journal, you can visit the PLOS booth to learn more about PLOS Biology, meet me and others from PLOS at our booth, number 544. We’re planning a meet the editor session from 12 til 1:30 pm on Monday 8th April; stop by to leave a message for me, or email me at biologue[at]plos.org, and we can arrange a time to chat.

We’ve gathered some examples of research articles in various aspects of cancer biology that have been published in PLOS Biology over the last few years, so if you’re interested in seeing some of the great research we publish, take a look at our AACR Collection 2013.

 

[1] ‘Annual Report to the Nation on the Status of Cancer, 1975–2009, Featuring the Burden and Trends in Human Papillomavirus (HPV)–Associated Cancers and HPV Vaccination Coverage Levels’
Ahmedin Jemal, Edgar P. Simard, Christina Dorell, Anne-Michelle Noone, Lauri E. Markowitz, Betsy Kohler, Christie Eheman, Mona Saraiya, Priti Bandi, Debbie Saslow, Kathleen A. Cronin, Meg Watson, Mark Schiffman, S. Jane Henley, Maria J. Schymura, Robert N. Anderson, David Yankey, and Brenda K. Edwards
JNCI J Natl Cancer Inst (2013) 105(3): 175-201 first published online January 7, 2013 doi:10.1093/jnci/djs491

 

 

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AACR Collection 2013

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journal.pbio.1001004.g001

Mejia R (2010) Cancer Courts Immune Response to Aid Growth. PLoS Biol 8(12): e1001004. doi:10.1371/journal.pbio.1001004

The Editorial team at PLOS Biology believes strongly that we are Open for a Reason; precisely so that research in areas of high importance reaches the widest audience.  Cancer research is one such area that should be as openly available, with associated data mineable and reusable, ideally in an open access, CC-BY journal as quickly as possible. Open access ensures the most expedient, economic and practical route to discovery and to developing potential therapeutic advances for the suite of diseases and conditions that we tend to over-simplify and apply one name to, cancer.

PLOS Biology is open for cancer research, and to highlight some of the discoveries we’ve published in this broad field, we’ve gathered together some research articles that cover various aspects of cancer biology published in PLOS Biology over the last few years, so if you’re interested in learning more about some of this great research take a look:

Essay:
Nonheritable Cellular Variability Accelerates the Evolutionary Processes of Cancer.
Frank SA, Rosner MR (2012)
PLOS Biol 10(4): e1001296. doi:10.1371/journal.pbio.1001296

Book review:
Cancer: The Whole Story.
Frank SA (2011)
PLOS Biol 9(4): e1001044. doi:10.1371/journal.pbio.1001044

Synopsis:
Cancer Courts Immune Response to Aid Growth.
Mejia R (2010)
PLOS Biol 8(12): e1001004. doi:10.1371/journal.pbio.1001004

And Corresponding Research Article:
Live Imaging of Innate Immune Cell Sensing of Transformed Cells in Zebrafish Larvae: Parallels between Tumor Initiation and Wound Inflammation.
Feng Y, Santoriello C, Mione M, Hurlstone A, Martin P (2010)
PLOS Biol 8(12): e1000562. doi:10.1371/journal.pbio.1000562

Research Articles:

ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer.
Kalyuga M, Gallego-Ortega D, Lee HJ, Roden DL, Cowley MJ, et al. (2012)
PLOS Biol 10(12): e1001461. doi:10.1371/journal.pbio.1001461

Stimulation of Host Bone Marrow Stromal Cells by Sympathetic Nerves Promotes Breast Cancer Bone Metastasis in Mice.
Citation: Campbell JP, Karolak MR, Ma Y, Perrien DS, Masood-Campbell SK, et al. (2012) PLOS Biol 10(7): e1001363. doi:10.1371/journal.pbio.1001363

Novel Role of NOX in Supporting Aerobic Glycolysis in Cancer Cells with Mitochondrial Dysfunction and as a Potential Target for Cancer Therapy.
Lu W, Hu Y, Chen G, Chen Z, Zhang H, et al. (2012)
PLOS Biol 10(5): e1001326. doi:10.1371/journal.pbio.1001326

ESRRA-C11orf20 Is a Recurrent Gene Fusion in Serous Ovarian Carcinoma.
Citation: Salzman J, Marinelli RJ, Wang PL, Green AE, Nielsen JS, et al. (2011)
PLOS Biol 9(9): e1001156. doi:10.1371/journal.pbio.1001156

Mesenchymal Transition and Dissemination of Cancer Cells Is Driven by Myeloid-Derived Suppressor Cells Infiltrating the Primary Tumor.
Toh B, Wang X, Keeble J, Sim WJ, Khoo K, et al. (2011)
PLOS Biol 9(9): e1001162. doi:10.1371/journal.pbio.1001162

HER2 Phosphorylation Is Maintained by a PKB Negative Feedback Loop in Response to Anti-HER2 Herceptin in Breast Cancer.
Gijsen M, King P, Perera T, Parker PJ, Harris AL, et al. (2010)
PLOS Biol 8(12): e1000563. doi:10.1371/journal.pbio.1000563

Targeting A20 Decreases Glioma Stem Cell Survival and Tumor Growth.
Hjelmeland AB, Wu Q, Wickman S, Eyler C, Heddleston J, et al. (2010)
PLOS Biol 8(2): e1000319. doi:10.1371/journal.pbio.1000319

If you visit the PLOS booth (booth #544) at the AACR Annual Meeting 2013, you can collect a printed version of this collection. We hope that you will enjoy these research and magazine articles from PLOS Biology; as with all of our content they are Open Access and freely available to all.

We encourage you to consider PLOS Biology as a high visibility venue for your future research. We are interested in all areas of cancer research traversing the bedside-to-bench spectrum, and we welcome translational studies. Our editorial model involves a partnership between professional and academic editors that guarantees our authors the best of both worlds; editorial expertise from the in-house team combined with the up-to-date specialised scientific knowledge of your colleagues who serve on our editorial board.

We hope you find this collection interesting. For more information about PLOS Biology and to submit your research, please visit www.plosbiology.org.

 

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Playing Roulette with Seven Sexes

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Have you ever watched “Seven Brides for Seven Brothers”? There are these seven brothers and, well you get the idea… But that was complicated enough with the two sexes that we boring old humans have – what if you had seven? That’s the exotic situation that the ciliate Tetrahymena finds itself in.

Tetrahymena [from Robinson R (2006) Ciliate Genome Sequence Reveals Unique Features of a Model Eukaryote. PLoS Biology 4(9):e304.]

We can only speculate as to how these creatures handle their private lives, but thanks to a paper just published in PLOS Biology we now know how they decide which of the seven sexes to be.

PLOS Biology recently published another example of ciliate madness – the bizarre 16,000 chromosomes of Oxytricha. Each generation that creature makes a “working copy” of its genome by a massive cut’n'paste job that results in almost one chromosome per gene. Tetrahymena does a similar thing, though not as spectacularly (a mere 225 chromosomes - as published in another PLOS Biology paper), and that’s where the sex decision is taken.

Marcella Cervantes, Eduardo Orias and colleagues now show how this happens, and it involves playing genomic roulette. Each generation two little Tetrahymena of different sex get together, turn up the Barry White, and cook up an unholy blend of their germline genomes. The offspring then makes its working copy (somatic) genome, and it’s around this time that it spins the wheel of fortune to decide what sex it’s going to be.

For an accessible account of how the authors actually went about their study, read Richard Robinson’s excellent Synopsis. However, I’m just going to cut to the chase and tell you how the funky roulette bit happens. While the baby Tetrahymena is rearranging the rest of its genome, one little bit of this genome is particularly busy. This region consists of a tight cluster of six back-to-back gene pairs (the authors use a strain that only has six sexes, just to make things inconvenient for bloggers and synopsis writers).

This array of genes is the roulette wheel. Each “number” comprises a pair of incomplete genes that should encode membrane-spanning proteins; the six pairs are clearly related to each other yet distinct, suggesting that they might do subtly different versions of the same job.

The relationship between Tetrahymena germline and somatic sex loci and their encoded proteins. Dotted lines indicate relationships between genes, rather than actual recombination events.

The relationship between Tetrahymena germline and somatic sex loci and their encoded proteins. Dotted lines indicate relationships between genes, rather than actual recombination events.

The fact that they’re incomplete is crucial. Comparing this germline array with the corresponding region of the “working copy” (somatic) genome reveals just how the game plays out. In each sex all but one of the gene pairs is deleted, leaving just one pair to determine the sex.  And the genomic cut’n'paste that does this neatly splices that remaining gene pair onto sequences at each end of the array, thereby completing the previously truncated genes and allowing them to be transcribed fruitfully. The selection of the remaining gene pair, and therefore of the sex, appears to be left entirely to chance, ensuring a good mix of sexes in the population.

Although this study stops with the identification of the genomic shenanigans, the assumption is presumably that these sex-specific pairs of transmembrane proteins somehow allow the sexes to recognise each other, or at least to avoid mating with the same sex. Even with their help, Tetrahymena dating must be a complicated business indeed.

 

ResearchBlogging.org

Cervantes, M., Hamilton, E., Xiong, J., Lawson, M., Yuan, D., Hadjithomas, M., Miao, W., & Orias, E. (2013). Selecting One of Several Mating Types through Gene Segment Joining and Deletion in Tetrahymena thermophila PLoS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001518

Robinson, R. (2013). Mating type determination in Tetrahymena: Last man standing PLOS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001522

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Are We Quorate Yet? Return to Bug Signalling

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You’re at a cheesy disco – it’s a large room, the lights are down, the music’s loud. But no one’s dancing. Because there are only five of you there and it’s embarrassing. More people arrive and drift across the dance floor self-consciously, but it’s not until you reach a critical density of bodies that feet start twitching and the spirit of Saturday Night Fever is re-born. Many decisions made by bacteria (and other organisms) depend on pretty much the same principles. Are enough of us here yet? Then let’s PARTY!!!!

This is called quorum sensing. And we have two papers in this week’s PLOS Biology that bring us closer to understanding how it works at the molecular level.

This is the picture I used three weeks ago. Now we’re talking about what happens after the “output” arrow at the bottom left (see my previous blog post for credits).

Three weeks ago I wrote a PLOS Biologue blog post that tied together two papers that looked at opposite ends of the signal histidine kinase (SK), a nifty rod-shaped molecule that translates environmental signals from the outside of a bug cell into a phosphate tag on the inside of that cell. The papers showed how it’s all about movement – the HAMP domains clicking from one form to another to signal ON/OFF status, and the business end (the kinase enzyme) swinging right round as the intervening rod buckles.

In that blog post I concentrated on the SK part of the system, telling you expressly to ignore the next bit – the Response Regulator (RR) – and just to think of it as a big “output” arrow.

Now, thanks to a nice bit of serendipity (and two more papers), I can invite you to stop ignoring what happens next, as we’ve just published a pair of papers that focus on a downstream set of molecular movements that determine how the RR integrates signals to help the bug make complex decisions.

First we need to complicate things a bit. We’ve already seen how the SK receives external information, and how its internal movements cause it to activate an enzyme that sticks a phosphate tag onto the RR protein, passing the message on. Two examples of RRs are Spo0F, which then goes on to trigger spore formation, and ComA, which regulates the ability of the bug to take up foreign DNA. Complicated enough? I’m afraid there’s more…

An external signal is transmitted via SK to RR, which should then pass it on. However, when levels of the secreted peptide Phr are low (left hand panel), a Rap protein binds to RR, blocking or deactivating it. When Phr levels are high (right hand panel), Rap can’t bind to RR, and RR is free to pass the signal on.

A decision such as whether to form a spore (or not) is a big commitment for a bacterium, so it needs to be able to bring several considerations to the table. One of the ways it does this is by integrating several signalling pathways to give it a final consensus outcome. SK passes on its phosphate tag to the correct RR protein in response to the signal that it has received. But there are other proteins that can then interfere with what RR does next. An example is the Rap family of proteins – some of these inactivate the RR by removing the phosphate that the SK has just put on there, while others bind to the RR and physically prevent it from passing the information on to the next part of the communication chain.

But when the bug makes Rap proteins, it simultaneously makes a tiny matching peptide called Phr. These are just a few amino acids long and are released from the cell into the environment. The bug then imports them back into the cell, where they bind to their specific Rap protein. Why go to the trouble of exporting and then re-importing a peptide? The key is that the amount of peptide in the outside world depends not only on how much that bug secretes, but also on how many of its mates are there also secreting the same peptide. The denser the bug population, the more Phr peptide there is to be imported and to bind to Rap. That’s the quorum-sensing bit.

But how does the tiny Phr peptide determine whether Rap does or doesn’t bind to the RR protein? Two new papers, just published in PLOS Biology, tell us exactly how. Research articles by Matt Neiditch and colleagues, and by Francisca Gallego del Sol and Alberto Marina, plus a comprehensive Primer by Marta Perego, now combine with those previous two papers to give us a vivid picture of the dynamism of this whole signalling pathway.

The free Rap protein (top) looks very similar in shape to when it’s bound to an RR protein such as ComA and Spo0F (bottom right). If the Rap protein is bound by its Phr peptide, however, its structure is altered (bottom right) so as to make interaction with RR proteins impossible (from Perego, PLOS Biology 2013).

Each paper gives us the detailed structure of a Phr peptide nestling in a slot in its Rap protein, plus a picture of the Rap protein without its Phr peptide. The authors can also compare these to structures of Rap proteins partnered with RR proteins ComA or Spo0F, both previously published in PLOS Biology in 2011 ( ComA and Spo0F papers - by Neiditch and colleagues again). It’s this comparison that reveals what’s going on. Although the free Rap protein has an almost identical shape to Rap that’s bound to an RR protein, the presence of Phr wreaks major structural changes. Once Phr fits into the slot, a distant part of the Rap molecule is re-structured (a phenomenon known as allostery) so that it is incompatible with RR.

This is all interesting enough for those working in the field, but it’s also potentially useful, as these structural studies could give us clues as to how we can manipulate the Phr-Rap signalling system to our benefit. Tricking the bacteria into believing that they’re quorate, even when they aren’t (or vice versa), could be advantageous in many therapeutic and biotechnological scenarios (for example, interfering with quorum sensing could disrupt biofilm formation, an important aspect of the lifestyle of some particularly nasty human pathogens). And given enough beers, most of us will dance on an empty floor.

ResearchBlogging.org

Parashar, V., Jeffrey, P., & Neiditch, M. (2013). Conformational Change-Induced Repeat Domain Expansion Regulates Rap Phosphatase Quorum-Sensing Signal Receptors PLoS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001512

ResearchBlogging.org

Gallego del Sol, F., & Marina, A. (2013). Structural Basis of Rap Phosphatase Inhibition by Phr Peptides PLoS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001511

Perego, M. (2013). Forty Years in the Making: Understanding the Molecular Mechanism of Peptide Regulation in Bacterial Development. PLoS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001516

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Positive Charges Clog the Ribosomal Tunnel

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Back when I was a lad we used to do lots of experiments, generate some data, analyse them, and try to come up with something interesting to say. Nowadays of course, experiments are for schmucks; the sheer quantity and availability of data means that you can cut out those first tedious and messy steps and just do the analysis on someone else’s data instead (assuming those data are openly available, of course).

That’s what Catherine Charneski and Laurence Hurst have done in an intriguing paper just published in this month’s PLOS Biology. You can also read about it in my accompanying Synopsis. The openly accessible data came from a 2009 Science paper from Jonathan Weissman’s lab, and this isn’t the first time that people have pored over this valuable dataset.

Question 1: The ribosome speeds along an mRNA, translating, but what slows it down?

The problem that the authors tackled relates to the ribosome, an incredible nanomachine that trundles along gene transcripts (mRNAs), translating them three letters at a time into the proteins that run most of the workings of the cell. The translation process requires little L-shaped adapters called tRNAs which line up the appropriate amino acids; the ribosome then glues the amino acids together and shoves the growing protein chain out through an exit tunnel in the back of the ribosome.

But does the ribosome move at a more-or-less constant rate along mRNA molecules, or is its speed is influenced by factors beyond its control? There are several reasons we might care about this. Evolutionary biologists are interested in the natural optimization of protein translation and the forces that shape it, while biotechnologists would like to optimize translation speed artificially to maximize protein productivity. The speed of translation is also known to affect how proteins fold and where they end up.

Question 2: …is it rare codons and their rare tRNAs?

We already know that translation speed is indeed highly variable, and it’s been thought that this is largely down to the abundance of the tRNA molecule needed to interpret each codon. Cells contain varying amounts of the different tRNAs, so a codon needing a rare tRNA might slow translation down because the ribosome has to hang around longer to encounter that tRNA, and vice versa.

 

Question 3: …is it mRNA secondary structure?

And what about mRNA secondary structure? If the ribosome needs to plough through a tangled segment of transcript, then we’d expect it to slow down as energy is expended to unravel the obstacle.

This is where large datasets come in handy; rather than relying on anecdotal data from individual transcripts, the recently developed technique of ribosome profiling gives us a snapshot of where the ribosomes are across all the transcripts in the cell. These data can be used to infer a high-resolution map of ribosome speeds that has the potential to tell us exactly what might be slowing ribosomes down.

Answer: None of the above – it’s the presence of positively charged amino acids (red beads) in the exit tunnel.

So what is the answer? In their paper, Charneski and Hurst show that codon/tRNA abundance and mRNA secondary structure don’t seem to matter very much. Instead, with amazing simplicity, the prime determinant of ribosome speed isn’t actually a direct feature of the mRNA itself, but a feature of the newly synthesised protein emerging from the exit tunnel. Here’s the key: if a ribosome has just translated one or more positively charged amino acids then it slows down.

The proposed explanation for this surprisingly simple outcome is that the positive charges interact electrostatically with the negatively charged lining of the ribosomal exit tunnel, gumming it up. The longer the run of positive charges, the greater the effect. As a throwaway, the authors also speculate about the polyA tails that decorate the ends of mRNAs; these would encode long strings of positively charged amino acids if translated, so might they have evolved as a sand-trap for runaway ribosomes?

An elegantly simple explanation for the observed variation in ribosome speed, a complex emergent consequence of an electrostatically charged exit tunnel, and a fine exemplar of data re-use. Nice paper.
ResearchBlogging.org

Charneski, C., & Hurst, L. (2013). Positively Charged Residues Are the Major Determinants of Ribosomal Velocity PLoS Biology, 11 (3) DOI: 10.1371/journal.pbio.1001508

 

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