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3. Chemical and microbiological assays of protein quality

Rationale of Scoring Procedures
Assays Utilizing the Amino Acid Profile Alone or in Combination with Protein Digestibility
Microbiological Assays
Advantages and Drawbacks

Rationale of Scoring Procedures

The role of dietary protein is to provide material for the synthesis of body protein and other metabolically important nitrogenous metabolises, as, for example, hormones of peptide-like nature and various active amino acid derivatives, such as the neurotransmitters serotonin and norepinephrine. All of the functions of dietary protein are essential for maintenance of health, but the process of body protein synthesis is usually considered to be quantitatively the most demanding in relation to amino acid utilization.

The nutritive value of a protein depends primarily on its capacity to satisfy the needs for nitrogen and essential amino acids. The nitrogen and amino acid requirements are, therefore, the logical yardsticks by which to measure protein quality, and precise knowledge about these requirements is basic for evaluation of the nutritional significance of dietary protein quality.

In 1946 Block and Mitchell introduced the concept of assessing the nutritional quality of a protein on the basis of its constituent amino acids and the value obtained was called chemical score (1). The method consists of calculating, by the use of tables or from direct analysis, the quantity of each essential amino acid contained in a protein or mixture of proteins. The values are expressed individually in proportion to the content of a corresponding amino acid in a suitable reference protein or amino acid pattern. The amino acid that shows the lowest proportion is called the limiting amino acid, and the ratio obtained is the score. The score for an individual protein food is defined as (mg of amino acid per g of test protein) / (mg of amino acid per g protein in reference pattern) or (mg of amino acid per g N in test protein) / (mg of amino acid per g N in reference pattern)

Originally, scores were expressed on a percentage scale. The present procedure is to express scores as fractions of unity. Scores and scoring patterns may be expressed in relation to protein or to nitrogen. The terms differ only in use of the conversion factor of nitrogen to protein. Considerable care is needed (chap. 2) when food table nitrogen data are converted to protein by the use of factors. In practice, however, the errors in scoring by the exclusive use of the N x 6.25 factor would not be large except with products such as single cell proteins that may contain high levels of nucleic acid nitrogen.

The most complete sets of amino acid data on foods (2, 3) express the values as mg/g N. The following example is calculated in this form.

Using data from table 5, together with the scoring pattern from table 2, we find the value for the Iysine in the cereal to be

Amino acid score = (mg of amino acid per g N in in test protein) / (mg of amino acid per g N in reference pattern )= 150/340 = 0.44

Calculations for total sulphur amino acids, threonine, and tryptophan give the values 1.09, 0.83, and 1.17 respectively. The value for Iysine is the lowest; thus, the amino acid score is 0.44, and the cereal is limited by Iysine.

For determination of the scores of a mixture of proteins, the calculation is, in effect, the weighted mean value for amino acids expressed on a per-gram-nitrogen basis. The original protein components in table 5 were limited by Iysine (cereal) and sulphur amino acids (legume and milk), but the final mixture is apparently limited by threonine.

Since the introduction by Block and Mitchell (1) of the concept of chemical score with egg protein as a standard, several other reference proteins have been introduced in the hope of obtaining better agreement between biological and chemical predictions of protein value.

The first major change in approach was substitution of a provisional pattern of amino acid requirements for the egg protein standard (4). A hypothetical reference protein derived from the pattern of human amino acid requirements was proposed as the standard for comparison and the term protein score was used instead of chemical score. Because the level of sulphur amino acids was considerably lower in the 1957 FAO reference protein (4) than in egg protein, improved agreement was found between scores and biological determinations of protein quality for proteins that were limiting in sulphur-containing amino acids. The pattern was tested for several years, but by 1965 its shortcomings had been recognized, and the joint FAD/WHO expert group recommended a new pattern, based on the essential amino acids of egg (5) but using a modified method of calculation. The new procedure was cumbersome and there were a number of theoretical objections to the scoring system. Therefore, the pattern was not widely adopted and many researchers continued to use the 1957 FAO pattern despite its shortcomings.

Table 5. Scoring Procedure for a Mixture of Cereal, Legume, and Milk Powder


Analytical data

Mixture composition g (w)

Mixture totals

N, g/kg (a)

Lys, mg/g N (b)

SAA, mg/gN (c)

Thr, mg/gN (d)

Trp, mg/g N (e)

N. g (wxa)/1 ,000 = n

Lys, mg (nxb)

SAA, mg (nxc)

Thr, mg (nxd)

Trp, mg (nxe)

Cereal 20 150 240 190 70 300 6.0 900 1,440 1,140 420
Legume 35 460 150 260 85 100 3.5 1,610 525 910 298
Milk powder 54 500 180 230 80 50 2.7 1,350 486 621 216
Totals             12.2 3,860 2,451 2,671 934
Amino acids per g N (total for each amino acid divided by ttal N)               316 201 219 77
Fao 1973 reference scoring pattrn   340 220 250 60            
Amino acids scores (amino acid per g N divided by reference value)               0.93 0.91 0.88 1.28

In the 1973 report Energy and Protein Requirements (6), discussed in chapter 1, the scoring pattern for determination of amino acid score was based on more recent evaluations of human amino acid requirements. The new scoring pattern was considered preferable to the use of whole egg or milk protein as the optimal pattern, although there was no experimental evidence that the provisional patterns based on what are now known as minimal requirements were superior to the "patterns found in good foods such as those of milk and egg."

Amino acid score was defined in this provisional pattern as milligrams of essential amino acids per gram of test protein divided by milligrams of essential amino acid per gram of reference protein, with the result multiplied by 100. The 1973 report states:

Provided that the lowest score obtained for any of the essential amino acids is used (i.e., the most limiting amino acid) the score may be taken as a first approximation to the probable efficiency of utilization of the test protein or mixture by children, and may permit a rough correction of protein requirements for the quality of dietary protein. This score may understimate the quality of protein for adults, whose essential amino acid needs per gram protein are lower. Although certain proteins may yield an apparent score above 100, the value cannot be used to adjust dietary protein requirements since N intakes would then be less than required to meet N requirements. [6]

So far, only scores based on the amount of Iysine, total sulphur amino acids, or tryptophan have been subjected to adequate biological testing. These are the amino acids found to be first limiting in most foods and diets. Therefore, only these three amino acids, and perhaps threonine, may need to be considered when calculating the scores of ordinary foodstuffs. A knowledge of the entire pattern is useful, however, in predicting the second and third limiting amino acids. The use of amino acid compositional data to predict protein nutritive value for adults has recently been reviewed by Bodwell (7).

To improve on the accuracy of protein scoring pracedures, chemically determined amino acid content may be corrected for biological availability by use of digestibility factors as discussed below.

Assays Utilizing the Amino Acid Profile Alone or in Combination with Protein Digestibility

Amino acid scores derived from the limiting amino acid should be comparable to the fraction of the absorbed nitrogen that is retained, i.e., the biological value (BV). The correlation between score and net protein utilization (NPU), which is a measure of the fraction of the intake nitrogen that is retained, i.e., an index inclusive of digestibility, will only be high when digestibility is high. Animal proteins are generally of high digestibility. For plant protein products of lower digestibility, it can, however, be advantageous to adjust amino acid scores by a digestibility factor to obtain an estimate of protein utilization. Estimated utilization will then equal the amino acid score multiplied by digestibility.

TABLE 6. Some Observed Protein Digestibilities

Protein source True protein digestibility* Approximate digestibility relative to    
  children adults egg or milk  
Egg 0.92, 0.97 0.97 1.00  
Milk 0.93, 0.91, 0.90 0.97 1.00  
Maize 0.82 0.76 0.82  
Rice, polished 0.85 0.84 0.90  
Wheat, whole - 0.79 0.93  
Wheat, refined 0.93 0.89 0.96  
Soybeans - 0.78 0.82  
Soy protein, isolated 0.92, 0.95, 0.88 --- 0.97
Mixed vegetable diets        
Corn + beans 0.78 0.82    
Wheat + soy protein 0.83 0.87    
Incaparina 0.77 0.81    
Indian rice diet 0.77 0.81    
Mixed vegetable/animal diets        
Corn, beans, milk 0.84 0.90    
Corn, soya, milk 0.94 1.00    
Corn-soya blend 0.87 0.92    
Indian rice diet + milk 0.87 0.92    
Fish flour, millet, and peanut flour 0.83 0.87    

TABLE 7. Amino Acid Scores of Some Proteins and Their Net Protein Utilization by Children 3 - 7 Years of Age

Protein Amino acid
Net protein utilization
at 2 - 3% at 4 - 5% at 6 - 7%
of dietary of dietary of dietary    
energy   energy   energy
Whole egg 1.00 0.87    
Human milk 1.00 0.95 0.85 0.95
Cow's milk 0.95 0.81 0.79 0.81
Soy bean 0.74      
milk 0.78 0.76 0.75  
flour     0.54  
toasted grits 0.72 0.80 0.67  
Sesame 0.50     0 54
Groundnut 0.65     0.57
Cottonseed 0.81     0.41

If digestibility data cannot be determined, literature values such as those shown in table 6 can be used to correct the score obtained.

Examples from the FAO 1973 report (6) of the close agreement between amino acid scores and NPU are given in table 7. It should be noted that protein was evaluated in these studies by NPU, which includes digestibility. Asindicated above, a more precise correlation would, in theory but not always in practice, be realized with BV. The discrepancy observed for cottonseed protein in table 7, where the amino acid score is 0.81, and the NPU for children is 0.41, suggests that some amino acids in cottonseed meal may be relatively unavailable.

Proteolytic enzymes have been used to predict digestibility, with both a pepsinpancreatin enzyme system (8) and a papain system (9) having been described. The results obtained agreed well with in vivo protein digestibility, as measured in the rat. A papain-trypsin system was subsequently developed (10) for determining in vitro protein digestibility and it was found that it correlated well with in vivo digestibility.

Earlier in vitro techniques (11) were modified and a ten-minute in vitro assay (12) for apparent protein digestibility that utilized the proteolytic enzymes trypsin, chymotrypsin, and amino-peptidase was described. A further modification was made by adding a fourth enzyme (bacterial protease), in order to be able to predict more accurately protein digestibility in animal protein foods. This procedure has been tested using more than 50 plant, animal, and combination protein foods (13).

Other tests have shown that the FAD/WHO scoring pattern (6) is effective in predicting the true limiting amino acid for the diets used (15, 16). Amino acid scores have been compared with determinations of protein value in humans in order to assess the quality of new protein sources for weanlings and young children (17). In general, the ranking of proteins was similar for both procedures.

The amino-acid-score procedure, even when it takes into account the degree of protein digestibility, considers only the first limiting amino acid; the second and third limiting amino acids may also be determinants of protein quality when present at low levels in the protein being investigated. Because of this the use of total essential amino acid content, instead of first limiting amino acid, to determine protein quality has been suggested (18).

Multiple regression equations based on computer-selected amino acids that provide estimates of protein efficiency ratio (PER) for foods containing meat ingredients have been suggested (19). Predictions from the model were found to be unreliable when examining plant-derived protein ingredients. This may have been because digestibility considerations were not taken into account, and also because PER may not be a suitable bioassay value for comparison. An enzymatic-ultrafiltrate digest (EUD) assay for predicting food protein nutritional quality has been described (20). The assay involves digesting a protein sample with pepsin-trypsinpancreatin and then determining the available amino acids by analysing the ultrafiltrate of the enzyme digest. The authors obtained a high correlation between the EUD index of ten food samples and their respective ratbased BV.

Because PER (chap. 4) is a time-consuming bioassay procedure, but is recognized as the "official" procedure for regulatory purposes in the United States and Canada, attempts have been made to predict PER by rapid laboratory techniques. PER was predicted for a variety of food proteins by expressing the essential amino acid profile of each sample as a percentage of a reference casein essential amino acid profile, after each was corrected for protein digestibility (12, 13). The index so calculated was termed C-PER (calculated protein efficiency ratio). Full details of data obtained using this procedure, and its comparison with data from the standard rat PER procedure, have recently been published (13). A complete description of the C-PER procedure involving both in vitro digestibility and amino acid scoring is given in chapter 8 (p. 97).

Microbiological Assays

These methods were first used to assay amino acids after acid hydrolysis of the protein, but they have also been used for determination of available amino acids (chap. 2) and for assay of protein quality.

Ford (21, 22) developed a method using Streptococcus zymogenes to measure available arginine, histidine, leucine, isoleucine, valine, methionine, and tryptophan. Unfortunately, the organism does not require Iysine; thus, neither total nor available Iysine could be determined. The organism can hydrolyse protein by its own enzymes, but the process is relatively slow. The assay can be improved if the protein is subjected to preliminary treatment with papain.

Another organism that is currently being used is Tetrabymena pyriformis, a ciliated protozoan that can ingest particles of food, thereby not having to rely entirely on soluble nutrients for growth. Furthermore, it requires the same ten essential amino acids as required by the growing rat (i.e., including Iysine), and thus shows an advantage over S. zymogenes.

T. pyriformis was used for determination of protein quality by Fernell and Rosen (23), and the response in relation to that obtained with casein was termed relative nutritive value ( RNV). This term has also been used more recently for a rat slope-ratio assay procedure. Both terms are defined in the Glossary.

As an index of growth, the organisms are counted and compared with those achieved with a protein or amino acid standard. Stott and Smith have outlined standardized conditions for the assay of available amino acids (24, 25), while Shorrock and Ford (26) have described procedures for measurement of available Iysine and methionine using this organism.

By combining a proteolytic enzyme partial-predigestion step along with growth of T. pyriformis on the hydrolysate, it was demonstrated (27-30) that Tetrabymena growth was highly correlated to PER values obtained with rats for selected foods. The Tetrabymena bioassay was shortened from 96 to 66 hours by substituting the more rapidly growing T. thermophila for T. pyriformis and by determining growth using a Coulter counter (12). The assay was further improved by development of two powdered mixes (basal medium and proteolytic enzyme + activator) for assaying the growth of T thermophila on food proteins (31). A simplified modification of this procedure (13) is described in chapter 8 (p. 98).

One of the major drawbacks to the Tetrabymena bioassay is the sensitivity of the protozoan to food additives and spices ( 13). Food additives such as the propionates, benzoates, sorbates, and the meat-curing adjuncts (nitrate, erythorbate, ascorbate) inhibit the growth of Tetrabymena either partially or completely when present in the food being assayed for its protein nutritional quality. It was also demonstrated that common spices, when present at levels as low as 0.01 per cent in a food being assayed by the Tetrabymena, could inhibit growth of the protozoan and hinder its ability to measure protein nutritional quality. Therefore this assay can only be used on foods whose composition is known and shown to be free of ingredients that will alter the ability of the organism to predict protein quality.

Advantages and Drawbacks

Chemical and microbiological procedures are subject to certain advantages and to several drawbacks. These are discussed in detail below.

Advantagas Speed, simplicity, and cost

Because animal and clinical facilities are not used, the procedure for scoring proteins and diets from amino acid data can be by far the simplest, fastest, and least expensive of all methods for determination of protein quality. The technique can range from the extremely simple, where literature data for amino acids and digestibility are used, to the more complex, where these data are obtained bY direct analyses using chemical or microbiological techniques, as have been described earlier.

Identification of the limiting amino acid

The limiting amino acid for a protein or a diet can readily be identified by the use of scoring procedures. With any animal assay, several trials are necessary wherein the protein is supplemented with various amino acids before the actual limiting amino acid can be identified. For the identification of the limiting amino acid by an amino acid score, the 1973 FAD/WHO pattern (6) has been shown to be superior to several previous patterns. As an example of this, two basal diets were experimentally supple" mented with amino acids to give 12 test diets. The true limiting amino acid, i.e., as determined biologically, was identified correctly in ten cases with the FAO/WHO 1973 pattern and in only three cases with the 1957 FAO reference pattern ( 15).

Estimation of complementary value

Once the amino acid composition of a protein is established, the complementary effect of that protein in combination with other proteins in the diet can be evaluated. This technique, together with simple computer programmes, can be used to develop complementary protein mixtures of maximum quality and/or maximum utilizable protein at minimum cost (32). The best mixtures obtained in this way would then be subjected to biological or clinical evaluation.

While scoring alone can often predict protein value in a satisfactory manner, in view of the limitations discussed below, improved accuracy may be obtained if digestibility data are incorporated.

Drawbacks Amino acid availability

As chemical analysis of amino acids is carried out after acid hydrolysis of the protein, the analysis yields total amino acid content. Some of the amino acids may, however, have been biologically unavailable. This lowered availability may or may not be reflected by impaired digestibility. The related degree of error varies with the food, but may be considerable in proteins and processed foods that have been heated. Problems of Iysine availability have been reviewed by Carpenter (33, 34), and have been discussed in chapter 2. While most work has been devoted to Iysine, other amino acids such as the sulphur amino acids can also be rendered unavailable. Cooking, even at elevated temperatures as in canning, generally does not affect amino acid availability. For other protein foods that have been extensively processed-for example, by dehydration-amino acid availability studies are essential; in these circumstances, scoring without considering availability data is unrealistic.

Amino acid release during digestion

It has been shown that amino acids are released at different rates during digestion of proteins (35, 36) and that the protein of the intestinal contents may originate predominantly from digestive secretions and sloughed mucosal cells (36) rather than from dietary protein. The rate of digestion may affect protein nutritional value (36), and there is within the gastrointestinal tract a large pool of labile protein that plays a part in overall protein metabolism. However, how greatly these factors affect nutritive value is still unclear.

Possible different utilization of amino acids and proteins

Amino acid mixtures or amino acid-supplemented protein foods may not be utilized as efficiently as proteins of the same amino acid composition. Rose and his associates (37) found that more dietary energy was needed to maintain nitrogen balance with amino acid mixtures than with whole protein of the same composition. It is postulated that the amino acid mixtures may have been absorbed more rapidly than the amino acids derived from protein, and that the rate of supply of energy may not have been adequate for efficient utilization of the amino acid mixture. In practice, however, the protein value of diets fortified with small quantities of amino acids agrees well with expectations, indicating that this effect is probably not of great importance in practical dietary evaluation.

Non-agreement for very poor-quality proteins

Although there is a good correlation between amino acid score and biological assay for proteins with a BV greater than about 0.40, the relationship varies with the limiting amino acid below this level (38). Proteins completely lacking Iysine can still have a BV equal to 0.40, and proteins lacking other amino acids can have values significantly above zero. The relationship changes below the value of 0.40 due to differing needs for maintenance and growth (39) and the capacity of organisms to adapt to low intakes of Iysine. The concept of scoring has been criticized on this basis; it has been stated (39) that if mixtures with a score of zero can have a BV of 0.40, one or the other method is invalid. Poor agreement can also occur at low levels of protein (40). At protein levels below about 50 g/kg (5 per cent), NPU was invariably higher than the score for a number of different limiting amino acids. In practice, however, very few proteins or actual dietaries have these very low levels of essential amino acids, and consequently more are in the range of good agreement between score and BV.

Role of non-specific nitrogen

Non-specific nitrogen may serve a biological function and can contribute toward biological usefulness, but its effect would not always be evident from amino acid score. Non-specific nitrogen has been defined by Kies (41) as nitrogen that is metabolically available and that can lead to minimal toxicity in the quantities used. It may include nitrogen furnished by the non-essential amino acids or excess essential amino acids, or by nonprotein sources such as urea or diammonium citrate. In most cases, the extra nitrogen would be accounted for as part of the total nitrogen and the score would be reduced. Agreement between the score and BV would be affected either positively or negatively, depending on the source used and the particular protein or amino acid in question. Non-specific nitrogen can affect apparent requirements for both protein and specific amino acids. Scrimshaw et al. (42) found that in adult subjects, milk protein could be diluted 20~25 per cent with nonspecific nitrogen before the protein nutrition, as indicated by nitrogen balance, was adversely affected. On a scoring basis, the dilution would have reduced the score for milk from 82 to 67; yet, protein needs were still being met. It should be emphasized that these data apPiY to adults and so the extent to which they are applicable to children needs further study,

The role of non-specific nitrogen in the nutrition of humans is still uncertain. Anomalies between score and biological determination of quality can occur despite the inclusion of added nitrogen as part of total nitrogen in the calculation of score.

Role of toxic materials

Because amino acid scoring examines only the level of amino acids in relation to total nitrogen, the presence of toxic materials in the food, could, if active at the level fed, affect the relationship between score and BV. In this context, the term "toxic" is used in its broadest sense (43) as any adverse physiological response that detracts from the nutritive value of a particular foodstuff. Toxic materials in a food would be either foreign chemicals accidentally present or natural components. A large discrepancy between score and BV suggests the presence of either toxic materials or non-available amino acids.

Thus, in summary, while amino acid scores alone overlook toxic factors, biological tests readily identify their presence. Toxic factors can frequently be eliminated by simple techniques such as soaking and/or cooking. Subsequent to the elimination or destruction of these factors, protein quality scores can be used to predict protein value. Care should be taken that the heat processing to eliminate toxins does not lead to heat damage of the protein and consequent unavailability of amino acids (chap. 2).

There are, on the other hand, problems in the reverse direction; compounds (flavours, spices, etc.) that are known not to be toxic for the rat or the human can inhibit the growth of a micro-organism used to measure protein quality and thereby yield erroneous data. Examples of this have previously been discussed (p. 33), but it can be seen that in this instance there could be agreement between scoring and a rat bioassay, with microbiological tests showing a large discrepancy.

Disproportionate amounts of amino acids

An important assumption made in the evaluation of the nutritional quality of protein by amino acid scoring is that the efficiency of utilization of dietary protein is a direct and linear function of the concentration of the limiting essential amino acid. This assumption implies that other essential or non-essential amino acids that may be provided in excess do not normally affect the utilization of the limiting amino acid. There is now considerable evidence to indicate that this assumption is not entirely valid (44-48). Similarly, amino acid balance may be responsible for protein quality values higher than expected from correction of essential amino acid deficiencies. For example, the high quality of Opaque-2 corn is due not only to the improved content of Iysine and tryptophan, but also to a lower leucine content. However, the quantitative extent to which the amino acid pattern of a diet may be unbalanced without affecting nitrogen utilization, and therefore protein quality, is not known.

Excess levels of the non-essential amino acids may also influence the overall utilization of dietary protein. This effect has, however, already been considered under the heading of non-specific nitrogen.

The extent to which amino acid imbalance can be created in human diets by the use of amino acid supplements is not clear, but the possibility deserves consideration. To quote Harper directly:

An amino acid supplement is of value only if the diet is primarily deficient in that amino acid. A supplement of an amino acid other than the one that is most deficient in the diet is at best innocuous and may, if the analogy to animal experiments is valid, depress food intake. This is likely to occur only if the diet is low in protein and marginal in some essential amino acids. Although such effects may not be serious, in view of the ability of animals to adapt to diets with amino acid imbalances, they are certainly not desirable and can be avoided readily by ensuring that any supplement provided makes the diet complete in all respects. [45]


The concept of a single pattern of amino acids that may be used as a yardstick in comparing the nutritive value of food and diets is subject to the same limitations and qualifications as is the concept of "protein quality." The relative proportions in which the essential amino acids are needed almost certainly depend upon the species, its physiological state, and interrelationships and interactions among the amino acids themselves. The pattern of amino acids required for maintenance may be quite different from the optimal pattern to support maximum growth. In addition, the limited accuracy of amino determinations in food and the problem of biological availability of the amino acids present further complications. However, the advantage of a method of dietary assessment in terms of amino acids is considerable, and is, in many circumstances, the only practical approach.


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