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Valorisation of food waste to biofuel: current trends and technological challenges
Corresponding author: Carol SK Lin carollin@cityu.edu.hk
School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
Sustainable Chemical Processes 2014, 2:22 doi:10.1186/s40508-014-0022-1
<More about author>
Introduction
Food waste is creating serious environmental and social problems in Hong Kong and across the world. According to a recent report released by the Hong Kong Environment Bureau, among the 9,000 tonnes of municipal solid waste that is thrown away everyday at landfills, 40% of which is composed of “putrescibles” [1]. These putrescibles are organic wastes that are known to create odour upon decomposition. Approximately, 90% of putrescibles are food wastes. Food waste can be raw, cooked, edible and inedible parts generated during production, storage distribution, and consumption of food stuffs. In 2011, Hong Kongers threw away approximately 3,600 tonnes of food waste everyday [1],[2]. Two third of the food waste was obtained from household; whereas, one third of food waste came from commercial and industrial sources. Hong Kong is not the only country generating large quantities of food waste. For instance, other developed cities like Taipei and Seoul are producing 182,000 tonnes/per year and 767,000 tonnes/per year of food wastes respectively [1],[2].
The food wastes produced in Hong Kong includes rotten fruits, vegetables, fish, poultry organs, fruits and vegetable peelings, meat, fish, shellfish shells, bones, food fats, sauces, condiments, soup pulp, Chinease medicinal pulp, egg shells, cheeses, ice cream, yogurts, tea leaves, teabags, coffee grounds, breads, cakes, biscuits, desserts, jam, different cereals, leftover of cooked food, BBQ raw or cooked leftovers, and pet food [1]. The Hong Kong Government plans to cut down the food waste that goes to landfill to approximately 40% by 2022. Landfills are the most common place for garbage deposition. Landfills spread offensive smell and are known to cause hazardous effects on people, animals, and the environment. Landfills are unsustainable as they produce methane which is a common green house gas. Furthermore, landfills also generate large amount of harmful leachate when rainwater falls on the garbage. This leachate can contaminate water and soil. Nevertheless, anaerobic digestion of food wastes that occurs naturally in the absence of oxygen employing bacteria can be used to produce biogas. Biogas is used as an energy source. Alternatively, food wastes can be valorized for the production of energy by using different common techniques such as composting, recycling and incineration. Although, these processes are capable of converting food waste into fuels and value-added products development of greener and advanced technologies are required [3].
Biofuel production is rapidly growing as the world encounters pollution problems due to burning of petroleum and coal based fuels. In addition, petroleum fuels are finite reserves and most of the petroleum reserves are geographically located in politically unstable countries. This reinforces the fact that alternative fuels are important from both environmental and energy security point of view. Along this line, many countries are formulating energy policies for the production of renewable energy.
At present, biofuels such as biodiesel and bioethanol are largely produced from edible food materials [4]. Various edible plant oils from soybean, rapeseed and canola oils are used for the preparation of biodiesel. Whereas, ethanol can be produced from a variety of feedstocks such as sugar cane, bagasse, sugar beet, grain, switchgrass, barley, potatoes, molasses, corn, stover, wheat and many other sources rich in carbohydrate [4],[5]. Chemical biodiesel production process is called transesterification [4],[5]. During transesterification, the tri-,di-and mono-glycerides react with methanol in the presence of a catalyst to produce biodiesel. On the other hand, the production of bioethanol process involves pretreatment, enzymatic hydrolysis, fermentation and distillation steps. Preparation of biofuels from edible food materials is attributed for the reason of food scarcity and a food vs fuel debate is already raging [6]. Alternatively, nonedible feedstocks can be used for the production of biofuels. Jatropha, Pongamia and other nonedible plant oils are already used for the preparation of biodiesel [5]. Along this line, nonedible lignocellulosic biomass is also employed for the production of bioethanol [7].
Food waste is a well-known nonedible source of lipids, carbohydrates, amino acids and phosphates [8],[9]. Reserach in our laboratory reveals that bakery and mixed food wastes contain significant amount of lipids and carbohydrates [8],[9]. Depending on the source of food waste the average lipid content was around 30% and the average carbohydrate content was around 50% [8],[9]. Different types of food wastes can be hydrolysed enzymatically to produce food hydrolysate and lipids [8],[9]. The food hydrolysate was rich in carbohydrate and can be used for the production of bioethanol; whereas, the obtained lipid can be converted to biodiesel (Figure 1).
thumbnailFigure 1. Recycling of food waste into biodiesel and bioethanol.
Along this line, noodle is a common starch based food material. In South Korea around 3 billion packages of instant noodle were consumed in 2011 and more than 2,100 tons of instant noodle residues were disposed as waste. Kim et al. have used instant noodle waste for the production of biofuels [10],[11]. Kim et al. recovered the oil from noodle waste by extraction using nonpolar hexane as a solvent. From 100 g of noodle waste 83 g of purified starch and 5 g of oil was obtained. The obtained oil free starch residue was used for simultaneous saccharification and fermentation process for the production of bioethanol [10],[11]. The hexane extract was evaporated and the obtained oil was reacted with methanol in the presence of acid and alkali catalysts for the preparation of biodiesel. One major limitation of this process is that the excess use of hexane during the extraction of oil from food waste [10],[11]. The Centers for Disease Control classifies n-hexane as a neurotoxin. It is also listed as a “hazardous air pollutant” by the Environmental Protection Agency as it helps in the formation of ozone at the ground level which is primarily responsible for smog. Nevertheless, these experiments demonstrate the potential utilization of waste noodle waste as a resource for biofuel production.
Research on the use of food wastes for the production of biofuel is becoming attractive in different countries. Sulaiman et al. have conceptualized a halal biorefinery for the production of fuels and value added products in Malaysia [12]. Yao et al. from the Chinese Academy of Sciences investigated the application of food waste to generate hydrolysates for the production of bioethanol [13]. In this context, potato peel is a well-known waste generated by the potato industries in Europe [14]. As reported by Christakopoulos.et al. this “no value” potato peel waste was converted to bioethanol using environmentally benign biocatalytic methods [13]. Researchers have also used household food waste for the production of bioethanol. During this process liquefaction and saccharification methods were employed to increase both ethanol production and productivity of the process [15]. Subsequently, fermentation of the remaining solids obtained from this process was performed to increase the overall yield of ethanol [15].
It is clear from the above discussion that environmental pollution and upcoming shortage of fossil fuels have turned the attention of researchers largely on the utilization of renewable feedstocks. Additionally, scientists and policy makers are devoting much efforts to use nonedible and zero cost food wastes for fuel and energy production to reduce the direct competition between fuel and food. It is known that food wastes are generated in large quantities and their handling is a challenge. As discussed earlier, these food wastes are potential resources as they contain substantial amount of carbohydrates and lipids. Thus, zero value food waste can be used as a resource for the production of low-cost biofuels. Research by various groups is currently underway for the production of biodiesel and bioethanol from food waste [16]-[22]. So far, the “proof of concept” for the synthesis and characterization of biofuels from different food wastes has been established [16]-[22].
Currently, technologies are available for the production of biodiesel and bioethanol in industrial scale. In this regard, a pilot scale production of ethanol from food waste using Saccharomyces cerevisiae H058 is already reported [22]. Nevertheless, low cost, greener and advanced technologies are needed for the production of fuels from food wastes [3],[23]. The industrial production of biofuel from food waste is largely depended on i) availability of food waste, ii) efficiency of hydrolyis process, iii) the amount of lipid and carbohydrate obtained from food waste, and iv) efficiency of fermentation and transesterification methods. In Hong Kong, Taiwan, Korea, US and in many other European countries plenty of food wastes are available. Thus, the future work should be primarily focused on large scale pretreatment and hydrolysis of food waste for production of lipid and sugar enriched hydrolysate. Several microorganisms and enzymes are known to hydrolyze food waste to carbohydrate, lipid, amino acids and phosphates. The catalytic efficiencies of the existing biocatalysts can be tested for the large scale hydrolysis of food wastes. Afterwards, the commercially available technologies can be employed for the production of biodiesel and bioethanol.
To make biofuels economically viable, the business and scientific communities and policy makers should come together to start a joint venture into the business of converting food waste into fuels. With proper financial and policy based supports from government, food waste biorefineries can be realized. In this context, it is particularly important to overcome the existing technological challenges of conventional food waste valorization methods. Simultaneously, it is crucial to develop environmental friendly and cost effective recycling methods that can convert food wastes into biofuels and chemicals [24]-[26]. Recently, combi-protein coated microcrystals of lipases are used for the production of biodiesel from oil of spent coffee grounds [27]. In this regard, both chemo- and biocatalytic methods can be explored for the preparation of biofuels from food waste [27]-[31].
The electronic version of this article is the complete one and can be found online at: http://www.sustainablechemicalprocesses.com/content/2/1/22
image source: 10 Green vehicles that run on food waste
Extending reference assembly models
Corresponding authors:
Deanna M Church deanna.church@personalis.com
Valerie A Schneider schneiva@ncbi.nlm.nih.gov
Richard Durbin rd@sanger.ac.uk
Paul Flicek flicek@ebi.ac.uk
Genome Biology 2015, 16:13 doi:10.1186/s13059-015-0587-3
Background
One of the flagship products of the Human Genome Project (HGP) was a high-quality human reference assembly [1]. This assembly, coupled with advances in low-cost, high-throughput sequencing, has allowed us to address previously inaccessible questions about population diversity, genome structure, gene expression and regulation [2]-[5]. It has become clear, however, that the original models used to represent the reference assembly inadequately represent our current understanding of genome architecture.
The first assembly models were designed for simple ‘linear’ genome sequences, with little sequence variation and even less structural diversity. The design fit the understanding of human variation at the time the HGP began [6]. The HGP constructed the reference assembly by collapsing sequences from over 50 individuals into a single consensus haplotype representation of each chromosome. Employing a clone-based approach, the sequence of each clone represented a single haplotype from a given donor. At clone boundaries, however, haplotypes could switch abruptly, creating a mosaic structure. This design introduced errors within regions of complex structural variation, when sequences unique to one haplotype prevented construction of clone overlaps. The assembly therefore inadvertently included multiple haplotypes in series in some regions [7]-[9].
The Genome Reference Consortium (GRC) began stewardship of the reference assembly in 2007. The GRC proposed a new assembly model that formalized the inclusion of ‘alternative sequence paths’ in regions with complex structural variation, and then released GRCh37 using this new model [10]. The release of GRCh37 also marked the deposition of the human reference assembly to an International Nucleotide Sequence Database Collaboration (INSDC) database, providing stable, trackable sequence identifiers, in the form of accession and version numbers, for all sequences in the assembly. The GRC developed an assembly model that was incorporated into the National Centre for Biotechnology Information (NCBI) and European Nucleotide Archive (ENA) assembly database that provides a stable identifier for the collection of sequences and the relationship between these sequences that comprise an assembly [11]. Subsequent minor assembly releases added a number of ‘fix patches’ that could be used to resolve mistakes in the reference sequence, as well as ‘novel patches’ that are new alternative sequence representations [10].
The new assembly model presents significant advances to the genomics community, but, to realize those advances, we must address many technical challenges. The new assembly model is neither haploid nor diploid - instead, it includes additional scaffold sequences, aligned to the chromosome assembly, that provide alternative sequence representations for regions of excess diversity. Widely used alignment programs, variant discovery and analysis tools, as well as most reporting formats, expect reads and features to have a single location in the reference assembly as they were developed using a haploid assembly model. Many alignment and analysis tools penalize reads that align to more than one location under the assumption that the location of these reads cannot be resolved owing to paralogous sequences in the genome. These tools do not distinguish allelic duplication, added by the alternative loci, from paralogous duplication found in the genome, thus confounding repeat and mappability calculations, paired-end placements and downstream interpretation of alignments in regions with alternative loci.
To determine the efforts needed to facilitate use of the full assembly, the GRC organized a workshop in conjunction with the 2014 Genome Informatics meeting in Cambridge, UK (http://www.slideshare.net/GenomeRef webcite). Participants identified challenges presented by the new assembly model and discussed ways forward that we describe here.
Towards the graph of human variation
A graph structure is a natural way to represent a population-based genome assembly, with branches in the graph representing all variation found within the source sequences. Most assembly programs internally use a graph representation to build the assembly, but ultimately produce a flattened structure for use by downstream tools [12]-[14]. Recently, formal proposals for representing a population-based reference graph have been described [15]-[17]. The newly formed Global Alliance for Genomics and Health (GA4GH) is leading an effort to formalize data structures for graph-based reference assemblies, but it will likely take years to develop the infrastructure and analysis tools needed to support these new structures and see their widespread adoption across the biological and clinical research communities [18].
The introduction of alternative loci into the assembly model provides a stepping-stone towards a full graph-based representation of a population-based reference genome. The alternative loci provided by the GRC are based on high-quality, finished sequence. Although it is not feasible to represent all known variation using the alternative locus scheme, this model does allow us to better represent regions with extreme levels of diversity. Alternative loci are not meant to represent all variation within a population, but rather provide an immediate solution for adding sequences missing from the chromosome assembly. In practice, alternative locus addition is limited by the availability of high-quality genomic sequence, and the GRC has focused on representing sequence at the most diverse regions, such as the major histocompatibility complex (MHC). The representation of all population variation is better suited to a graph-based representation. The high quality of the sequence at these locations provides robust data to test graph implementations. Additionally, because both NCBI and Ensembl have annotated these sequences, we can also begin to address how to annotate graph structures at these complex loci.
While GRCh37 had only three regions containing nine alternative locus sequences, GRCh38 has 178 regions containing 261 alternative locus sequences, collectively representing 3.6 Mbp of novel sequence and over 150 genes not represented in the primary assembly (Table 1). The increased level of alternative sequence representation intensifies the urgency to develop new analysis methods to support inclusion of these sequences. Inclusion of all sequences in the reference assembly allows us to better analyze these regions with potentially modest updates to currently used tools and reporting structures. Although the addition of the alternative loci to current analysis pipelines might lead to only modest gains in analysis power on a genome-wide scale, some loci will see considerable improvement owing to the addition of significant amounts of sequence that cannot be represented accurately in the chromosome assembly (Figure 1).
Omission of the novel sequence contained in the alternative loci can lead to off-target sequence alignments, and thus incorrect variant calls or other errors, when a sample containing the alternative allele is sequenced and aligned to only the primary assembly. Using reads simulated from the unique portion of the alternative loci, we found that approximately 75% of the reads had an off-target alignment when aligned to the primary assembly alone. This finding was consistent using different alignment methods [10]. The 1000 Genomes Project also observed the detrimental effect of missing sequences and developed a ‘decoy’ sequence dataset in an effort to minimize off-target alignments [19],[20]. Much of this decoy has now been incorporated into GRCh38, and analysis of reads taken from 1000 Genomes samples that previously mapped only to the decoy shows that approximately 70% of these now align to the full GRCh38, with approximately 1% of these reads aligning only to the alternative loci (Figure 2).
We foresee many computational approaches that allow the inclusion of all assembly sequences in analysis pipelines. To better support exploration in this area, we propose some improvements to standard practices and data structures that will facilitate future development.
Enhancement of standard reporting formats (such as BAM/CRAM, VCF/BCF, GFF3) so that they can accommodate features with multiple locations. Doing so while maintaining the allelic relationship between these features is crucial [21]-[24].
Adoption of standard sequence identifiers for sequence analysis and reporting. Using shorthand identifiers (for example, ‘chr1’ or ‘1’) to indicate the sequence is imprecise and also ignores the presence of other sequences in the assembly. In many cases, other top-level sequences, such as unlocalized scaffolds, patches and alternative loci, have a chromosome assignment but not chromosome coordinates. These sequences are independent of the chromosome assembly coordinate system and have their own coordinate space. Alternative loci are related to the chromosome coordinates through alignment to the chromosome assembly. Developing a structure that treats all top-level sequences as first-class citizens during analysis is an important step towards adopting use of the full assembly in analysis pipelines.
Curation of multiple sequence alignments of the alternative loci to each other and the primary path. Currently, pairwise alignments of the alternative loci to the chromosome assembly are available to provide the allelic relationship between the alternative locus and the chromosome. However, these pairwise alignments do not allow for the comparison of alternative loci in a given region to each other. These alignments can also be used to develop graph structures. The relationship of the allelic sequences within a region helps define the assembly structure, and the community should work from a single set of alignments. These should be distributed with the GRC assembly releases.
Recently, the GRC has released a track hub [25] that allows for the distribution of GRC data using standard track names and content (http://ngs.sanger.ac.uk/production/grit/track_hub/hub.txt webcite). Additionally, the GRC has created a GitHub page to track development of tools and resources that facilitate use of the full assembly (https://github.com/GenomeRef/SoftwareDevTracking webcite).
Concluding remarks
As we gain understanding of biological systems, we must update the models we use to represent these data. This can be difficult when the model supports common infrastructure and analysis tools used by a large swath of the scientific community. However, this growth is crucial in order to move the scientific community forward. While adoption of this new model will take substantial effort, doing so is an important step for the human genetics and broader genomics communities. We now have an opportunity and imperative to revisit old assumptions and conventions to develop a more robust analysis framework. The use of all sequences included in the reference will allow for improved genomic analyses and understanding of genomic architecture. Additionally, this new assembly model allows us to take a small step towards the realization of a graph-based assembly representation. The evolution of the assembly model allows us to improve our understanding of genomic architecture and provides a framework for boosting our understanding of how this architecture impacts human development and disease.
The electronic version of this article is the complete one and can be found online at: http://genomebiology.com/2015/16/1/13
image source: http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/human/
Deanna M Church deanna.church@personalis.com
Valerie A Schneider schneiva@ncbi.nlm.nih.gov
Richard Durbin rd@sanger.ac.uk
Paul Flicek flicek@ebi.ac.uk
Genome Biology 2015, 16:13 doi:10.1186/s13059-015-0587-3
One of the flagship products of the Human Genome Project (HGP) was a high-quality human reference assembly [1]. This assembly, coupled with advances in low-cost, high-throughput sequencing, has allowed us to address previously inaccessible questions about population diversity, genome structure, gene expression and regulation [2]-[5]. It has become clear, however, that the original models used to represent the reference assembly inadequately represent our current understanding of genome architecture.
The first assembly models were designed for simple ‘linear’ genome sequences, with little sequence variation and even less structural diversity. The design fit the understanding of human variation at the time the HGP began [6]. The HGP constructed the reference assembly by collapsing sequences from over 50 individuals into a single consensus haplotype representation of each chromosome. Employing a clone-based approach, the sequence of each clone represented a single haplotype from a given donor. At clone boundaries, however, haplotypes could switch abruptly, creating a mosaic structure. This design introduced errors within regions of complex structural variation, when sequences unique to one haplotype prevented construction of clone overlaps. The assembly therefore inadvertently included multiple haplotypes in series in some regions [7]-[9].
The Genome Reference Consortium (GRC) began stewardship of the reference assembly in 2007. The GRC proposed a new assembly model that formalized the inclusion of ‘alternative sequence paths’ in regions with complex structural variation, and then released GRCh37 using this new model [10]. The release of GRCh37 also marked the deposition of the human reference assembly to an International Nucleotide Sequence Database Collaboration (INSDC) database, providing stable, trackable sequence identifiers, in the form of accession and version numbers, for all sequences in the assembly. The GRC developed an assembly model that was incorporated into the National Centre for Biotechnology Information (NCBI) and European Nucleotide Archive (ENA) assembly database that provides a stable identifier for the collection of sequences and the relationship between these sequences that comprise an assembly [11]. Subsequent minor assembly releases added a number of ‘fix patches’ that could be used to resolve mistakes in the reference sequence, as well as ‘novel patches’ that are new alternative sequence representations [10].
The new assembly model presents significant advances to the genomics community, but, to realize those advances, we must address many technical challenges. The new assembly model is neither haploid nor diploid - instead, it includes additional scaffold sequences, aligned to the chromosome assembly, that provide alternative sequence representations for regions of excess diversity. Widely used alignment programs, variant discovery and analysis tools, as well as most reporting formats, expect reads and features to have a single location in the reference assembly as they were developed using a haploid assembly model. Many alignment and analysis tools penalize reads that align to more than one location under the assumption that the location of these reads cannot be resolved owing to paralogous sequences in the genome. These tools do not distinguish allelic duplication, added by the alternative loci, from paralogous duplication found in the genome, thus confounding repeat and mappability calculations, paired-end placements and downstream interpretation of alignments in regions with alternative loci.
To determine the efforts needed to facilitate use of the full assembly, the GRC organized a workshop in conjunction with the 2014 Genome Informatics meeting in Cambridge, UK (http://www.slideshare.net/GenomeRef webcite). Participants identified challenges presented by the new assembly model and discussed ways forward that we describe here.
Towards the graph of human variation
A graph structure is a natural way to represent a population-based genome assembly, with branches in the graph representing all variation found within the source sequences. Most assembly programs internally use a graph representation to build the assembly, but ultimately produce a flattened structure for use by downstream tools [12]-[14]. Recently, formal proposals for representing a population-based reference graph have been described [15]-[17]. The newly formed Global Alliance for Genomics and Health (GA4GH) is leading an effort to formalize data structures for graph-based reference assemblies, but it will likely take years to develop the infrastructure and analysis tools needed to support these new structures and see their widespread adoption across the biological and clinical research communities [18].
The introduction of alternative loci into the assembly model provides a stepping-stone towards a full graph-based representation of a population-based reference genome. The alternative loci provided by the GRC are based on high-quality, finished sequence. Although it is not feasible to represent all known variation using the alternative locus scheme, this model does allow us to better represent regions with extreme levels of diversity. Alternative loci are not meant to represent all variation within a population, but rather provide an immediate solution for adding sequences missing from the chromosome assembly. In practice, alternative locus addition is limited by the availability of high-quality genomic sequence, and the GRC has focused on representing sequence at the most diverse regions, such as the major histocompatibility complex (MHC). The representation of all population variation is better suited to a graph-based representation. The high quality of the sequence at these locations provides robust data to test graph implementations. Additionally, because both NCBI and Ensembl have annotated these sequences, we can also begin to address how to annotate graph structures at these complex loci.
While GRCh37 had only three regions containing nine alternative locus sequences, GRCh38 has 178 regions containing 261 alternative locus sequences, collectively representing 3.6 Mbp of novel sequence and over 150 genes not represented in the primary assembly (Table 1). The increased level of alternative sequence representation intensifies the urgency to develop new analysis methods to support inclusion of these sequences. Inclusion of all sequences in the reference assembly allows us to better analyze these regions with potentially modest updates to currently used tools and reporting structures. Although the addition of the alternative loci to current analysis pipelines might lead to only modest gains in analysis power on a genome-wide scale, some loci will see considerable improvement owing to the addition of significant amounts of sequence that cannot be represented accurately in the chromosome assembly (Figure 1).
Omission of the novel sequence contained in the alternative loci can lead to off-target sequence alignments, and thus incorrect variant calls or other errors, when a sample containing the alternative allele is sequenced and aligned to only the primary assembly. Using reads simulated from the unique portion of the alternative loci, we found that approximately 75% of the reads had an off-target alignment when aligned to the primary assembly alone. This finding was consistent using different alignment methods [10]. The 1000 Genomes Project also observed the detrimental effect of missing sequences and developed a ‘decoy’ sequence dataset in an effort to minimize off-target alignments [19],[20]. Much of this decoy has now been incorporated into GRCh38, and analysis of reads taken from 1000 Genomes samples that previously mapped only to the decoy shows that approximately 70% of these now align to the full GRCh38, with approximately 1% of these reads aligning only to the alternative loci (Figure 2).
We foresee many computational approaches that allow the inclusion of all assembly sequences in analysis pipelines. To better support exploration in this area, we propose some improvements to standard practices and data structures that will facilitate future development.
Enhancement of standard reporting formats (such as BAM/CRAM, VCF/BCF, GFF3) so that they can accommodate features with multiple locations. Doing so while maintaining the allelic relationship between these features is crucial [21]-[24].
Adoption of standard sequence identifiers for sequence analysis and reporting. Using shorthand identifiers (for example, ‘chr1’ or ‘1’) to indicate the sequence is imprecise and also ignores the presence of other sequences in the assembly. In many cases, other top-level sequences, such as unlocalized scaffolds, patches and alternative loci, have a chromosome assignment but not chromosome coordinates. These sequences are independent of the chromosome assembly coordinate system and have their own coordinate space. Alternative loci are related to the chromosome coordinates through alignment to the chromosome assembly. Developing a structure that treats all top-level sequences as first-class citizens during analysis is an important step towards adopting use of the full assembly in analysis pipelines.
Curation of multiple sequence alignments of the alternative loci to each other and the primary path. Currently, pairwise alignments of the alternative loci to the chromosome assembly are available to provide the allelic relationship between the alternative locus and the chromosome. However, these pairwise alignments do not allow for the comparison of alternative loci in a given region to each other. These alignments can also be used to develop graph structures. The relationship of the allelic sequences within a region helps define the assembly structure, and the community should work from a single set of alignments. These should be distributed with the GRC assembly releases.
Recently, the GRC has released a track hub [25] that allows for the distribution of GRC data using standard track names and content (http://ngs.sanger.ac.uk/production/grit/track_hub/hub.txt webcite). Additionally, the GRC has created a GitHub page to track development of tools and resources that facilitate use of the full assembly (https://github.com/GenomeRef/SoftwareDevTracking webcite).
Concluding remarks
As we gain understanding of biological systems, we must update the models we use to represent these data. This can be difficult when the model supports common infrastructure and analysis tools used by a large swath of the scientific community. However, this growth is crucial in order to move the scientific community forward. While adoption of this new model will take substantial effort, doing so is an important step for the human genetics and broader genomics communities. We now have an opportunity and imperative to revisit old assumptions and conventions to develop a more robust analysis framework. The use of all sequences included in the reference will allow for improved genomic analyses and understanding of genomic architecture. Additionally, this new assembly model allows us to take a small step towards the realization of a graph-based assembly representation. The evolution of the assembly model allows us to improve our understanding of genomic architecture and provides a framework for boosting our understanding of how this architecture impacts human development and disease.
The electronic version of this article is the complete one and can be found online at: http://genomebiology.com/2015/16/1/13
image source: http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/human/
Cell culture models for study of differentiated adipose cells
Correspondence: Martin Clynes martin.clynes@dcu.ie
National Institute for Cellular Biotechnology, Dublin City University, Glasnevin, Dublin 9, Ireland
Stem Cell Research & Therapy 2014, 5:137 doi:10.1186/scrt527
More about author:
Prof. Martin Clynes @ NICB
Commentary
There is increasing interest in the use of adipose cells, both brown and white types, not least because the obesity epidemic dictates a need for increased research on adipose tissue and lipid metabolism. The paper by Balducci and colleagues – a collaboration between five Italian groups – reports the immortalisation, by lentiviral transduction, of human adipose-derived stromal cells [1].
Adipose cells are an important resource for biomedical research, partly because of the ready availability of human surgical material and the fact that they can be used to generate mesenchymal stem cells [2] – which themselves have interesting differentiation potential, for example towards a hepatocyte phenotype [3] – and even pluripotent stem cells [4]. Adipose-derived stem cells have been reported to differentiate into osteoblasts, chondrocytes, myocytes and neurons, as well as back to adipocytes, depending on the culture conditions [5]. Pluripotent stem cells [6,7], including induced pluripotent stem cells [8], can be differentiated in vitro into cells with multiple phenotypic characteristics of adipose cells, including specifically brown adipose cells [7].
It is interesting to note that telomerase expression in bone marrow stromal cells resulted in enhanced bone formation [9,10]. Another approach to generating large populations of adipose cells in vitro is to use viral immortalisation, as has been also achieved in other systems such as bone marrow progenitor cells [11].
Balducci and colleagues report diversity in differentiation potential between cell lines immortalised with different gene combinations, which is in itself an interesting observation, but it is not entirely clear what the cellular or molecular basis for this may be or whether it is a purely random observation [1]. Whatever the mechanism, human adipose-derived stromal cells co-transduced with human telomerase reverse transcriptase and human papilloma virus E6/E7 generated immortalised cells that retained the capacity to differentiate down osteogenic and adipogenic lineages and to produce angiogenesis-related proteins. Cells transduced with human telomerase reverse transcriptase alone or with human telomerase reverse transcriptase and Simian virus 40 did not retain these capacities to the same extent. The availability of immortal cell lines that closely resemble adipose-derived stromal cells contributes a useful new resource for those working on this fascinating cell type.
Nevertheless, it is important to bear in mind that, as in all such cases, these adipose cells are not normal cells identical to their parental finite-lifespan progenitors – transduced cells are unlikely to be acceptable for therapeutic use except perhaps in the terminal stages of life-threatening diseases. Indeed, Balducci and colleagues acknowledge this limitation and report on chromosomal aberrations and unbalanced translocations in the transduced cells. However, there is no doubt that the availability of these immortalised human adipose-derived stromal cell lines will significantly facilitate research on this interesting and relatively neglected cell type, and availability of these cell lines will help to answer more rapidly questions about their biology and expedite their application in cell therapy/tissue engineering, even if the cells eventually used for therapy will most probably be of primary origin rather than cell lines. The availability of large numbers of these cells that can be easily grown also offers the potential for discovery of additional autocrine, paracrine and endocrine factors which these cells may produce, but at levels too low to be detected from small-scale, limited-lifespan primary cultures, and this, in the end, could be the most valuable legacy from this interesting paper.
The availability of these different sources of adipose cells provides a much-expanded toolkit for research on adipose cells in vitro, and should make a significant impact on the progress of obesity research and on our understanding of adipose cell differentiation.
The electronic version of this article is the complete one and can be found online at: http://stemcellres.com/content/5/6/137
See related research by Balducci et al.,
Immortalization of human adipose-derived stromal cells: production of cell lines with high growth rate, mesenchymal marker expression and capability to secrete high levels of angiogenic factors
image source: The surprising science of fat: you can get fatter and become healthier. PLOS Blogs
National Institute for Cellular Biotechnology, Dublin City University, Glasnevin, Dublin 9, Ireland
Stem Cell Research & Therapy 2014, 5:137 doi:10.1186/scrt527
More about author:
Prof. Martin Clynes @ NICB
Commentary
There is increasing interest in the use of adipose cells, both brown and white types, not least because the obesity epidemic dictates a need for increased research on adipose tissue and lipid metabolism. The paper by Balducci and colleagues – a collaboration between five Italian groups – reports the immortalisation, by lentiviral transduction, of human adipose-derived stromal cells [1].
Adipose cells are an important resource for biomedical research, partly because of the ready availability of human surgical material and the fact that they can be used to generate mesenchymal stem cells [2] – which themselves have interesting differentiation potential, for example towards a hepatocyte phenotype [3] – and even pluripotent stem cells [4]. Adipose-derived stem cells have been reported to differentiate into osteoblasts, chondrocytes, myocytes and neurons, as well as back to adipocytes, depending on the culture conditions [5]. Pluripotent stem cells [6,7], including induced pluripotent stem cells [8], can be differentiated in vitro into cells with multiple phenotypic characteristics of adipose cells, including specifically brown adipose cells [7].
It is interesting to note that telomerase expression in bone marrow stromal cells resulted in enhanced bone formation [9,10]. Another approach to generating large populations of adipose cells in vitro is to use viral immortalisation, as has been also achieved in other systems such as bone marrow progenitor cells [11].
Balducci and colleagues report diversity in differentiation potential between cell lines immortalised with different gene combinations, which is in itself an interesting observation, but it is not entirely clear what the cellular or molecular basis for this may be or whether it is a purely random observation [1]. Whatever the mechanism, human adipose-derived stromal cells co-transduced with human telomerase reverse transcriptase and human papilloma virus E6/E7 generated immortalised cells that retained the capacity to differentiate down osteogenic and adipogenic lineages and to produce angiogenesis-related proteins. Cells transduced with human telomerase reverse transcriptase alone or with human telomerase reverse transcriptase and Simian virus 40 did not retain these capacities to the same extent. The availability of immortal cell lines that closely resemble adipose-derived stromal cells contributes a useful new resource for those working on this fascinating cell type.
Nevertheless, it is important to bear in mind that, as in all such cases, these adipose cells are not normal cells identical to their parental finite-lifespan progenitors – transduced cells are unlikely to be acceptable for therapeutic use except perhaps in the terminal stages of life-threatening diseases. Indeed, Balducci and colleagues acknowledge this limitation and report on chromosomal aberrations and unbalanced translocations in the transduced cells. However, there is no doubt that the availability of these immortalised human adipose-derived stromal cell lines will significantly facilitate research on this interesting and relatively neglected cell type, and availability of these cell lines will help to answer more rapidly questions about their biology and expedite their application in cell therapy/tissue engineering, even if the cells eventually used for therapy will most probably be of primary origin rather than cell lines. The availability of large numbers of these cells that can be easily grown also offers the potential for discovery of additional autocrine, paracrine and endocrine factors which these cells may produce, but at levels too low to be detected from small-scale, limited-lifespan primary cultures, and this, in the end, could be the most valuable legacy from this interesting paper.
The availability of these different sources of adipose cells provides a much-expanded toolkit for research on adipose cells in vitro, and should make a significant impact on the progress of obesity research and on our understanding of adipose cell differentiation.
The electronic version of this article is the complete one and can be found online at: http://stemcellres.com/content/5/6/137
See related research by Balducci et al.,
Immortalization of human adipose-derived stromal cells: production of cell lines with high growth rate, mesenchymal marker expression and capability to secrete high levels of angiogenic factors
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